Construction of a large scale integrated map of macrophage pathogen recognition and effector systems

<p>Abstract</p> <p>Background</p> <p>In an effort to better understand the molecular networks that underpin macrophage activation we have been assembling a map of relevant pathways. Manual curation of the published literature was carried out in order to define the components of these pathways and the interactions between them. This information has been assembled into a large integrated directional network and represented graphically using the modified Edinburgh Pathway Notation (mEPN) scheme.</p> <p>Results</p> <p>The diagram includes detailed views of the toll-like receptor (TLR) pathways, other pathogen recognition systems, NF-kappa-B, apoptosis, interferon signalling, MAP-kinase cascades, MHC antigen presentation and proteasome assembly, as well as selected views of the transcriptional networks they regulate. The integrated pathway includes a total of 496 unique proteins, the complexes formed between them and the processes in which they are involved. This produces a network of 2,170 nodes connected by 2,553 edges.</p> <p>Conclusions</p> <p>The pathway diagram is a navigable visual aid for displaying a consensus view of the pathway information available for these systems. It is also a valuable resource for computational modelling and aid in the interpretation of functional genomics data. We envisage that this work will be of value to those interested in macrophage biology and also contribute to the ongoing Systems Biology community effort to develop a standard notation scheme for the graphical representation of biological pathways.</p

The in silico macrophage: toward a better understanding of inflammatory disease

Macrophages function as sentinel, cell-regulatory hubs capable of initiating, perpetuating and contributing to the resolution of an inflammatory response, following their activation from a resting state. Highly complex and varied gene expression programs within the macrophage enable such functional diversity. To investigate how programs of gene expression relate to the phenotypic attributes of the macrophage, the development of in silico modeling methods is needed. Such models need to cover multiple scales, from molecular pathways in cell-autonomous immunity and intercellular communication pathways in tissue inflammation to whole organism response pathways in systemic disease. Here, we highlight the potential of in silico macrophage modeling as an amenable and important yet under-exploited tool in aiding in our understanding of the immune inflammatory response. We also discuss how in silico macrophage modeling can help in future therapeutic strategies for modulating both the acute protective effects of inflammation (such as host defense and tissue repair) and the harmful chronic effects (such as autoimmune diseases).Comment: 7 pages plus 1 figur

Visualisation of BioPAX Networks using BioLayout Express (3D).

BioLayout Express (3D) is a network analysis tool designed for the visualisation and analysis of graphs derived from biological data. It has proved to be powerful in the analysis of gene expression data, biological pathways and in a range of other applications. In version 3.2 of the tool we have introduced the ability to import, merge and display pathways and protein interaction networks available in the BioPAX Level 3 standard exchange format. A graphical interface allows users to search for pathways or interaction data stored in the Pathway Commons database. Queries using either gene/protein or pathway names are made via the cPath2 client and users can also define the source and/or species of information that they wish to examine. Data matching a query are listed and individual records may be viewed in isolation or merged using an 'Advanced' query tab. A visualisation scheme has been defined by mapping BioPAX entity types to a range of glyphs. Graphs of these data can be viewed and explored within BioLayout as 2D or 3D graph layouts, where they can be edited and/or exported for visualisation and editing within other tools

Controlling the Response: Predictive Modeling of a Highly Central, Pathogen-Targeted Core Response Module in Macrophage Activation

We have investigated macrophage activation using computational analyses of a compendium of transcriptomic data covering responses to agonists of the TLR pathway, Salmonella infection, and manufactured amorphous silica nanoparticle exposure. We inferred regulatory relationship networks using this compendium and discovered that genes with high betweenness centrality, so-called bottlenecks, code for proteins targeted by pathogens. Furthermore, combining a novel set of bioinformatics tools, topological analysis with analysis of differentially expressed genes under the different stimuli, we identified a conserved core response module that is differentially expressed in response to all studied conditions. This module occupies a highly central position in the inferred network and is also enriched in genes preferentially targeted by pathogens. The module includes cytokines, interferon induced genes such as Ifit1 and 2, effectors of inflammation, Cox1 and Oas1 and Oasl2, and transcription factors including AP1, Egr1 and 2 and Mafb. Predictive modeling using a reverse-engineering approach reveals dynamic differences between the responses to each stimulus and predicts the regulatory influences directing this module. We speculate that this module may be an early checkpoint for progression to apoptosis and/or inflammation during macrophage activation

DC-ATLAS: a systems biology resource to dissect receptor specific signal transduction in dendritic cells

BACKGROUND: The advent of Systems Biology has been accompanied by the blooming of pathway databases. Currently pathways are defined generically with respect to the organ or cell type where a reaction takes place. The cell type specificity of the reactions is the foundation of immunological research, and capturing this specificity is of paramount importance when using pathway-based analyses to decipher complex immunological datasets. Here, we present DC-ATLAS, a novel and versatile resource for the interpretation of high-throughput data generated perturbing the signaling network of dendritic cells (DCs). RESULTS: Pathways are annotated using a novel data model, the Biological Connection Markup Language (BCML), a SBGN-compliant data format developed to store the large amount of information collected. The application of DC-ATLAS to pathway-based analysis of the transcriptional program of DCs stimulated with agonists of the toll-like receptor family allows an integrated description of the flow of information from the cellular sensors to the functional outcome, capturing the temporal series of activation events by grouping sets of reactions that occur at different time points in well-defined functional modules. CONCLUSIONS: The initiative significantly improves our understanding of DC biology and regulatory networks. Developing a systems biology approach for immune system holds the promise of translating knowledge on the immune system into more successful immunotherapy strategies

The mEPN scheme: an intuitive and flexible graphical system for rendering biological pathways

<p>Abstract</p> <p>Background</p> <p>There is general agreement amongst biologists about the need for good pathway diagrams and a need to formalize the way biological pathways are depicted. However, implementing and agreeing how best to do this is currently the subject of some debate.</p> <p>Results</p> <p>The modified Edinburgh Pathway Notation (mEPN) scheme is founded on a notation system originally devised a number of years ago and through use has now been refined extensively. This process has been primarily driven by the author's attempts to produce process diagrams for a diverse range of biological pathways, particularly with respect to immune signaling in mammals. Here we provide a specification of the mEPN notation, its symbols, rules for its use and a comparison to the proposed Systems Biology Graphical Notation (SBGN) scheme.</p> <p>Conclusions</p> <p>We hope this work will contribute to the on-going community effort to develop a standard for depicting pathways and will provide a coherent guide to those planning to construct pathway diagrams of their biological systems of interest.</p

Modelling and analysis of macrophage activation pathways

Macrophages are present in virtually all tissues and account for approximately 10% of all body mass. Although classically credited as the scavenger cells of innate immune system, ridding a host of pathogenic material and cellular debris though their phagocytic function, macrophages also play a crucial role in embryogenesis, homeostasis, and inflammation. De-regulation of macrophage function is therefore implicated in the progression of many disease states including cancer, arthritis, and atherosclerosis to name just a few. The diverse range of activities of this cell can be attributed to its exceptional phenotypic plasticity i.e. it is capable of adapting its physiology depending on its environment; for instance in response to different types of pathogens, or specific cocktail of cytokines detected. This plasticity is exemplified by the macrophages capacity to adjust rapidly its transcriptional profile in response to a given stimulus. This includes interferons which are a group of cytokines capable of activating the macrophage by interacting with their cognate receptors on the cell. The different classes of interferons activate downstream signalling cascades, eventually leading to the expression (as well as repression) of hundreds of genes. To begin to fully understand the properties of a dynamic cell such as the macrophage arguably requires a holistic appreciation of its constituents and their interactions. Systems biology investigations aim to escape from a gene-centric view of biological systems. As such this necessitates the development of better ways to order, display, mine and analyse biological information, from our knowledge of protein interactions and the systems they form, to the output of high throughput technologies. The primary objectives of this research were to further characterise the signalling mechanisms driving macrophages activation, especially in response to type-I and type- II interferons, as well as lipopolysaccharide (LPS), using a ‘systems-level’ approach to data analysis and modelling. In order to achieve this end I have explored and developed methods for the executing a ‘systems-level’ analysis. Specifically the questions addressed included: (a) How does one begin to formalise and model the existing knowledge of signalling pathways in the macrophage? (b) What are the similarities and differences between the macrophage response to different types of interferon (namely interferon-β (IFN-β) and interferon-γ (IFN-γ))? (c) How is the macrophage transcriptome affected by siRNA targeting of key regulators of the interferon pathway? (d) To what extent does a model of macrophage signalling aid interpretation of the data generated from functional genomics screens? There is general agreement amongst biologists about the need for high-quality pathway diagrams and a method to formalize the way biological pathways are depicted. In an effort to better understand the molecular networks that underpin macrophage activation an in-silico model or ‘map’ of relevant pathways was constructed by extracting information from published literature describing the interactions of individual constituents of this cell and the processes they modulate (Chapter-2). During its construction process many challenges of converting pathway knowledge into computationally-tractable yet ‘understandable’ diagrams, were to be addressed. The final model comprised 2,170 components connected by 2,553 edges, and is to date the most comprehensive formalised model of macrophage signalling. Nevertheless this still represents just a modest body of knowledge on the cell. Related to the pathway modelling efforts was the need for standardising the graphical depiction of biology in order to achieve these ends. The methods for implementing this and agreeing a ‘standard’ has been the subject of some debate. Described herein (in Chapter-3) is the development of one graphical notation system for biology the modified Edinburgh Pathway Notation (mEPN). By constructing the model of macrophage signalling it has been possible to test and extensively refine the original notation into an intuitive, yet flexible scheme capable of describing a range of biological concepts. The hope is that the mEPN development work will contribute to the on-going community effort to develop and agree a standard for depicting pathways and the published version will provide a coherent guide to those planning to construct pathway diagrams of their biological systems of interest. With a desire to better understand the transcriptional response of primary mouse macrophages to interferon stimulation, genome wide expression profiling was performed and an explorative-network based method applied for analysing the data generated (Chapter-4). Although transcriptomics data pertaining to interferon stimulation of macrophages is not entirely novel, the network based analysis of it provided an alternative approach to visualise, mine and interpret the output. The analysis revealed overlap in the transcriptional targets of the two classes of interferon, as well as processes preferentially induced by either cytokine; for example MHC-Class II antigen processing and presentation by IFN-γ, and an anti-proliferative signature by IFN-β. To further investigate the contribution of individual proteins towards generating the type-I (IFN-β) response, short interfering RNA (siRNA) were employed to repress the expression of selected target genes. However in macrophages and other cells equipped with pathogen detection systems the act of siRNA trasfection can itself induce a type-I interferon response. It was therefore necessary to contend with this autocrine production of IFN-β and optimise an in vitro assay for studying the contribution of siRNA induced gene-knock downs to the interferon response (described in Chapter-5). The final assay design incorporated LPS stimulation of the macrophages, as a means of inducing IFN-β autonomously of the transfection induced type-I response. However genome-wide expression analysis indicated the targeted gene knock-downs did not perturb the LPS response in macrophages on this occasion. The optimisation process underscored the complexities of performing siRNA gene knockdown studies in primary macrophages. Furthermore a more thorough understanding of the transcriptional response of macrophages to stimulation by interferon or by LPS was required. Therefore the final investigations of this thesis (Chapter-6) explore the transcriptional changes over a 24 hour time-course of macrophage activation by IFN-β, IFN-γ, or LPS and the contribution of the macrophage pathway model in interpreting the response to the three stimuli. Taken together the work described in this thesis highlight the advances to be made from a systems-based approach to visualisation, modelling and analysis of macrophage signalling

Identification of novel candidate genes for regulation of follicle selection in the avian ovary

Selective breeding of chickens for high growth rate and other production traits has led to the modern commercial broiler, a bird that has the genetic potential for reaching an average body weight of 2.7kg within 6 weeks of hatch. However, the breeding stock for modern broilers has to be feed controlled in order to lay large numbers of viable hatching eggs. Broiler breeders, when fed ad libitum, have a propensity to produce internal ovulations, double-yolked, misshapen or shell-less eggs. This is due to the release of multiple ova at ovulation, which results in a significant loss of production. Feed control has been shown to mitigate this effect but welfare concerns have been raised as to the side-effects for the birds. The main objective of this research was to determine the genetic basis for the regulation of ovarian follicle selection and its dysfunction in ad libitum-fed broiler breeders, and how this might be addressed by genetic selection to limit the impact on the management and welfare of future broiler breeders. A multi-layered statistical, expression profiling and cluster analysis of ovarian gene expression data from a microarray study was carried out to identify candidate genes for further study.Key stages of development were investigated for feed restricted and ad libitum-fed broiler breeders. Several gene candidate genes were validated by qPCR in a comparison of different ovarian tissues in layer type hens for subsequent analysis in broiler breeders. Sequencing of the founders of an Advanced Intercross Line (AIL) of commercial broiler breeders and White Leghorn layers was performed covering 3 regions of each of the primary candidate genes in order to identify genetic variation that could account for differences in follicle number between broilers and layers. Expression data from a microarray study highlighted a number of potential candidate genes for regulation of follicle development. One of these genes, Platelet Derived Growth Factor Receptor Like (PDGFRL), shares significant sequence homology with the active domains of Platelet Derived Growth Factor Receptor β. Expression profiling in layers showed peak PDGFRL expression in 5-6 mm follicles and the F2 follicle (P <0.001). PDGFRL was also up-regulated in response to ad libitum feeding in broiler breeders in 6-8 mm follicles (P<0.016), the point at which follicle selection and recruitment is considered to occur. In addition to this, while PDGFRL expression remains relatively constant between tissues under ad libitum conditions, it shows a clear reduction in expression (P <0.001) in prehierarchical follicles relative to the stroma and the F1 follicle under feed restriction. This observation is consistent with results from the original microarray study. Sequencing of the AIL Founders highlighted several SNPs in the broiler that have the potential to be used as markers for incorporation into commercial selection programs. EST alignment in preparation for targeted sequencing of PDGFRL also highlighted three potential forms of the protein, each with a different 5’ starting sequence. Initial investigation has shown all three to be expressed in ovarian follicles. QPCR in a panel of 13 tissues shows marked differences between the 3 variants, implying different and perhaps specialised roles for each. The PDGFR family has a potential role in steroidogenesis, and the expression profiling, combined with the clear effect on expression from ad libitum feeding in broiler breeders, suggest that PDGFRL is a strong candidate for involvement in the regulation of follicle development GDF9, shown to be associated with multiple ovulation in sheep, and FSH receptor, a mediator of neuroendocrine signalling to the ovary, were also investigated. They behaved as expected in layer type birds but both showed significant differential expression (P = 0.005 and 0.018 respectively) as a result of ad libitum feeding in broiler breeders. Though these two genes have been extensively investigated, these are previously unobserved effects. SNPs have also been identified in these genes which have the potential to be used as markers for incorporation into commercial selection programs. To fully exploit these results, additional investigation is recommended to confirm these results in commercial populations and to determine how they can be employed to best effect