Toxicology knowledge graph for structural birth defects

BACKGROUND

Birth defects are functional and structural abnormalities that impact about 1 in 33 births in the United States. They have been attributed to genetic and other factors such as drugs, cosmetics, food, and environmental pollutants during pregnancy, but for most birth defects there are no known causes.

METHODS

To further characterize associations between small molecule compounds and their potential to induce specific birth abnormalities, we gathered knowledge from multiple sources to construct a reproductive toxicity Knowledge Graph (ReproTox-KG) with a focus on associations between birth defects, drugs, and genes. Specifically, we gathered data from drug/birth-defect associations from co-mentions in published abstracts, gene/birth-defect associations from genetic studies, drug- and preclinical-compound-induced gene expression changes in cell lines, known drug targets, genetic burden scores for human genes, and placental crossing scores for small molecules.

RESULTS

Using ReproTox-KG and semi-supervised learning (SSL), we scored >30,000 preclinical small molecules for their potential to cross the placenta and induce birth defects, and identified >500 birth-defect/gene/drug cliques that can be used to explain molecular mechanisms for drug-induced birth defects. The ReproTox-KG can be accessed via a web-based user interface available at https://maayanlab.cloud/reprotox-kg . This site enables users to explore the associations between birth defects, approved and preclinical drugs, and all human genes.

CONCLUSIONS

ReproTox-KG provides a resource for exploring knowledge about the molecular mechanisms of birth defects with the potential of predicting the likelihood of genes and preclinical small molecules to induce birth defects.

Extending and using anatomical vocabularies in the stimulating peripheral activity to relieve conditions project

The stimulating peripheral activity to relieve conditions (SPARC) program is a US National Institutes of Health-funded effort to improve our understanding of the neural circuitry of the autonomic nervous system (ANS) in support of bioelectronic medicine. As part of this effort, the SPARC project is generating multi-species, multimodal data, models, simulations, and anatomical maps supported by a comprehensive knowledge base of autonomic circuitry. To facilitate the organization of and integration across multi-faceted SPARC data and models, SPARC is implementing the findable, accessible, interoperable, and reusable (FAIR) data principles to ensure that all SPARC products are findable, accessible, interoperable, and reusable. We are therefore annotating and describing all products with a common FAIR vocabulary. The SPARC Vocabulary is built from a set of community ontologies covering major domains relevant to SPARC, including anatomy, physiology, experimental techniques, and molecules. The SPARC Vocabulary is incorporated into tools researchers use to segment and annotate their data, facilitating the application of these ontologies for annotation of research data. However, since investigators perform deep annotations on experimental data, not all terms and relationships are available in community ontologies. We therefore implemented a term management and vocabulary extension pipeline where SPARC researchers may extend the SPARC Vocabulary using InterLex, an online vocabulary management system. To ensure the quality of contributed terms, we have set up a curated term request and review pipeline specifically for anatomical terms involving expert review. Accepted terms are added to the SPARC Vocabulary and, when appropriate, contributed back to community ontologies to enhance ANS coverage. Here, we provide an overview of the SPARC Vocabulary, the infrastructure and process for implementing the term management and review pipeline. In an analysis of >300 anatomical contributed terms, the majority represented composite terms that necessitated combining terms within and across existing ontologies. Although these terms are not good candidates for community ontologies, they can be linked to structures contained within these ontologies. We conclude that the term request pipeline serves as a useful adjunct to community ontologies for annotating experimental data and increases the FAIRness of SPARC data.

Representing Normal and Abnormal Physiology as Routes of Flow in ApiNATOMY

We present (i) the ApiNATOMY workflow to build knowledge models of biological connectivity, as well as (ii) the ApiNATOMY TOO map, a topological scaffold to organize and visually inspect these connectivity models in the context of a canonical architecture of body compartments. In this work, we outline the implementation of ApiNATOMY’s knowledge representation in the context of a large-scale effort, SPARC, to map the autonomic nervous system. Within SPARC, the ApiNATOMY modeling effort has generated the SCKAN knowledge graph that combines connectivity models and TOO map. This knowledge graph models flow routes for a number of normal and disease scenarios in physiology. Calculations over SCKAN to infer routes are being leveraged to classify, navigate and search for semantically-linked metadata of multimodal experimental datasets for a number of cross-scale, cross-disciplinary projects.

The SPARC DRC: Building a Resource for the Autonomic Nervous System Community

The Data and Resource Center (DRC) of the NIH-funded SPARC program is developing databases, connectivity maps, and simulation tools for the mammalian autonomic nervous system. The experimental data and mathematical models supplied to the DRC by the SPARC consortium are curated, annotated and semantically linked via a single knowledgebase. A data portal has been developed that allows discovery of data and models both via semantic search and via an interface that includes Google Map-like 2D flatmaps for displaying connectivity, and 3D anatomical organ scaffolds that provide a common coordinate framework for cross-species comparisons. We discuss examples that illustrate the data pipeline, which includes data upload, curation, segmentation (for image data), registration against the flatmaps and scaffolds, and finally display via the web portal, including the link to freely available online computational facilities that will enable neuromodulation hypotheses to be investigated by the autonomic neuroscience community and device manufacturers.

Sialic acid-binding immunoglobulin-like lectin (Sigelac)-15 is a rapidly internalised cell-surface antigen expressed by acute myeloid leukaemia cells

Sialic acid-binding immunoglobulin-like lectin (Siglec)-15 has recently been identified as a critical tumour checkpoint, augmenting the expression and function of programmed death-ligand 1. We raised a monoclonal antibody, A9E8, specific for Siglec-15 using phage display. A9E8 stained myeloid leukaemia cell lines and peripheral cluster of differentiation (CD)33+ blasts and CD34+ leukaemia stem cells from patients with acute myeloid leukaemia (AML). By contrast, there was minimal expression on healthy donor leucocytes or CD34+ stem cells from non-AML donors, suggesting targeting Siglec-15 may have significant therapeutic advantages over its fellow Siglec CD33. After binding, A9E8 was rapidly internalised (half-life of 180 s) into K562 cells. Antibodies to Siglec-15 therefore hold therapeutic potential for AML treatment.

Knowledge Representation for Multi-Scale Physiology Route Modeling

We present a framework for the topological and semantic assembly of multiscale physiology route maps. The framework, called ApiNATOMY, consists of a knowledge representation (KR) model and a set of knowledge management (KM) tools. Using examples of ApiNATOMY route maps, we present a KR format that is suitable for the analysis and visualization by KM tools. The conceptual KR model provides a simple method for physiology experts to capture process interactions among anatomical entities. In this paper, we outline the KR model, modeling format, and the KM procedures to translate concise abstraction-based specifications into fully instantiated models of physiology processes.

Model annotation and discovery with the Physiome Model Repository

BACKGROUND

Mathematics and Phy sics-based simulation models have the potential to help interpret and encapsulate biological phenomena in a computable and reproducible form. Similarly, comprehensive descriptions of such models help to ensure that such models are accessible, discoverable, and reusable. To this end, researchers have developed tools and standards to encode mathematical models of biological systems enabling reproducibility and reuse, tools and guidelines to facilitate semantic description of mathematical models, and repositories in which to archive, share, and discover models. Scientists can leverage these resources to investigate specific questions and hypotheses in a more efficient manner.

RESULTS

We have comprehensively annotated a cohort of models with biological semantics. These annotated models are freely available in the Physiome Model Repository (PMR). To demonstrate the benefits of this approach, we have developed a web-based tool which enables users to discover models relevant to their work, with a particular focus on epithelial transport. Based on a semantic query, this tool will help users discover relevant models, suggesting similar or alternative models that the user may wish to explore or use.

CONCLUSION

The semantic annotation and the web tool we have developed is a new contribution enabling scientists to discover relevant models in the PMR as candidates for reuse in their own scientific endeavours. This approach demonstrates how semantic web technologies and methodologies can contribute to biomedical and clinical research. The source code and links to the web tool are available at https://github.com/dewancse/model-discovery-tool.

Automated PDF highlighting to support faster curation of literature for Parkinson's and Alzheimer's disease

Neurodegenerative disorders such as Parkinson's and Alzheimer's disease are devastating and costly illnesses, a source of major global burden. In order to provide successful interventions for patients and reduce costs, both causes and pathological processes need to be understood. The ApiNATOMY project aims to contribute to our understanding of neurodegenerative disorders by manually curating and abstracting data from the vast body of literature amassed on these illnesses. As curation is labour-intensive, we aimed to speed up the process by automatically highlighting those parts of the PDF document of primary importance to the curator. Using techniques similar to those of summarisation, we developed an algorithm that relies on linguistic, semantic and spatial features. Employing this algorithm on a test set manually corrected for tool imprecision, we achieved a macro F 1 -measure of 0.51, which is an increase of 132% compared to the best bag-of-words baseline model. A user based evaluation was also conducted to assess the usefulness of the methodology on 40 unseen publications, which reveals that in 85% of cases all highlighted sentences are relevant to the curation task and in about 65% of the cases, the highlights are sufficient to support the knowledge curation task without needing to consult the full text. In conclusion, we believe that these are promising results for a step in automating the recognition of curation-relevant sentences. Refining our approach to pre-digest papers will lead to faster processing and cost reduction in the curation process.

Database URL

https://github.com/KHP-Informatics/NapEasy.

Roadmap for cardiovascular circulation model

Computational models of many aspects of the mammalian cardiovascular circulation have been developed. Indeed, along with orthopaedics, this area of physiology is one that has attracted much interest from engineers, presumably because the equations governing blood flow in the vascular system are well understood and can be solved with well-established numerical techniques. Unfortunately, there have been only a few attempts to create a comprehensive public domain resource for cardiovascular researchers. In this paper we propose a roadmap for developing an open source cardiovascular circulation model. The model should be registered to the musculo-skeletal system. The computational infrastructure for the cardiovascular model should provide for near real-time computation of blood flow and pressure in all parts of the body. The model should deal with vascular beds in all tissues, and the computational infrastructure for the model should provide links into CellML models of cell function and tissue function. In this work we review the literature associated with 1D blood flow modelling in the cardiovascular system, discuss model encoding standards, software and a model repository. We then describe the coordinate systems used to define the vascular geometry, derive the equations and discuss the implementation of these coupled equations in the open source computational software OpenCMISS. Finally, some preliminary results are presented and plans outlined for the next steps in the development of the model, the computational software and the graphical user interface for accessing the model.

A physiome interoperability roadmap for personalized drug development

The goal of developing therapies and dosage regimes for characterized subgroups of the general population can be facilitated by the use of simulation models able to incorporate information about inter-individual variability in drug disposition (pharmacokinetics), toxicity and response effect (pharmacodynamics). Such observed variability can have multiple causes at various scales, ranging from gross anatomical differences to differences in genome sequence. Relevant data for many of these aspects, particularly related to molecular assays (known as '-omics'), are available in online resources, but identification and assignment to appropriate model variables and parameters is a significant bottleneck in the model development process. Through its efforts to standardize annotation with consequent increase in data usability, the human physiome project has a vital role in improving productivity in model development and, thus, the development of personalized therapy regimes. Here, we review the current status of personalized medicine in clinical practice, outline some of the challenges that must be overcome in order to expand its applicability, and discuss the relevance of personalized medicine to the more widespread challenges being faced in drug discovery and development. We then review some of (i) the key data resources available for use in model development and (ii) the potential areas where advances made within the physiome modelling community could contribute to physiologically based pharmacokinetic and physiologically based pharmacokinetic/pharmacodynamic modelling in support of personalized drug development. We conclude by proposing a roadmap to further guide the physiome community in its on-going efforts to improve data usability, and integration with modelling efforts in the support of personalized medicine development.

The Human Physiome: how standards, software and innovative service infrastructures are providing the building blocks to make it achievable

Reconstructing and understanding the Human Physiome virtually is a complex mathematical problem, and a highly demanding computational challenge. Mathematical models spanning from the molecular level through to whole populations of individuals must be integrated, then personalized. This requires interoperability with multiple disparate and geographically separated data sources, and myriad computational software tools. Extracting and producing knowledge from such sources, even when the databases and software are readily available, is a challenging task. Despite the difficulties, researchers must frequently perform these tasks so that available knowledge can be continually integrated into the common framework required to realize the Human Physiome. Software and infrastructures that support the communities that generate these, together with their underlying standards to format, describe and interlink the corresponding data and computer models, are pivotal to the Human Physiome being realized. They provide the foundations for integrating, exchanging and re-using data and models efficiently, and correctly, while also supporting the dissemination of growing knowledge in these forms. In this paper, we explore the standards, software tooling, repositories and infrastructures that support this work, and detail what makes them vital to realizing the Human Physiome.

Bioinformatics Mining and Modeling Methods for the Identification of Disease Mechanisms in Neurodegenerative Disorders

Since the decoding of the Human Genome, techniques from bioinformatics, statistics, and machine learning have been instrumental in uncovering patterns in increasing amounts and types of different data produced by technical profiling technologies applied to clinical samples, animal models, and cellular systems. Yet, progress on unravelling biological mechanisms, causally driving diseases, has been limited, in part due to the inherent complexity of biological systems. Whereas we have witnessed progress in the areas of cancer, cardiovascular and metabolic diseases, the area of neurodegenerative diseases has proved to be very challenging. This is in part because the aetiology of neurodegenerative diseases such as Alzheimer´s disease or Parkinson´s disease is unknown, rendering it very difficult to discern early causal events. Here we describe a panel of bioinformatics and modeling approaches that have recently been developed to identify candidate mechanisms of neurodegenerative diseases based on publicly available data and knowledge. We identify two complementary strategies-data mining techniques using genetic data as a starting point to be further enriched using other data-types, or alternatively to encode prior knowledge about disease mechanisms in a model based framework supporting reasoning and enrichment analysis. Our review illustrates the challenges entailed in integrating heterogeneous, multiscale and multimodal information in the area of neurology in general and neurodegeneration in particular. We conclude, that progress would be accelerated by increasing efforts on performing systematic collection of multiple data-types over time from each individual suffering from neurodegenerative disease. The work presented here has been driven by project AETIONOMY; a project funded in the course of the Innovative Medicines Initiative (IMI); which is a public-private partnership of the European Federation of Pharmaceutical Industry Associations (EFPIA) and the European Commission (EC).

TARM1 Is a Novel Leukocyte Receptor Complex-Encoded ITAM Receptor That Costimulates Proinflammatory Cytokine Secretion by Macrophages and Neutrophils

We identified a novel, evolutionarily conserved receptor encoded within the human leukocyte receptor complex and syntenic region of mouse chromosome 7, named T cell-interacting, activating receptor on myeloid cells-1 (TARM1). The transmembrane region of TARM1 contained a conserved arginine residue, consistent with association with a signaling adaptor. TARM1 associated with the ITAM adaptor FcRγ but not with DAP10 or DAP12. In healthy mice, TARM1 is constitutively expressed on the cell surface of mature and immature CD11b(+)Gr-1(+) neutrophils within the bone marrow. Following i.p. LPS treatment or systemic bacterial challenge, TARM1 expression was upregulated by neutrophils and inflammatory monocytes and TARM1(+) cells were rapidly recruited to sites of inflammation. TARM1 expression was also upregulated by bone marrow-derived macrophages and dendritic cells following stimulation with TLR agonists in vitro. Ligation of TARM1 receptor in the presence of TLR ligands, such as LPS, enhanced the secretion of proinflammatory cytokines by macrophages and primary mouse neutrophils, whereas TARM1 stimulation alone had no effect. Finally, an immobilized TARM1-Fc fusion protein suppressed CD4(+) T cell activation and proliferation in vitro. These results suggest that a putative T cell ligand can interact with TARM1 receptor, resulting in bidirectional signaling and raising the T cell activation threshold while costimulating the release of proinflammatory cytokines by macrophages and neutrophils.

The Open Physiology workflow: modeling processes over physiology circuitboards of interoperable tissue units

A key challenge for the physiology modeling community is to enable the searching, objective comparison and, ultimately, re-use of models and associated data that are interoperable in terms of their physiological meaning. In this work, we outline the development of a workflow to modularize the simulation of tissue-level processes in physiology. In particular, we show how, via this approach, we can systematically extract, parcellate and annotate tissue histology data to represent component units of tissue function. These functional units are semantically interoperable, in terms of their physiological meaning. In particular, they are interoperable with respect to [i] each other and with respect to [ii] a circuitboard representation of long-range advective routes of fluid flow over which to model long-range molecular exchange between these units. We exemplify this approach through the combination of models for physiology-based pharmacokinetics and pharmacodynamics to quantitatively depict biological mechanisms across multiple scales. Links to the data, models and software components that constitute this workflow are found at http://open-physiology.org/.

Computational Horizons In Cancer (CHIC): Developing Meta- and Hyper-Multiscale Models and Repositories for In Silico Oncology - a Brief Technical Outline of the Project

This paper briefly outlines the aim, the objectives, the architecture and the main building blocks of the ongoing large scale integrating transatlantic research project CHIC (http://chic-vph.eu/).

Transcriptional diversity during lineage commitment of human blood progenitors

Blood cells derive from hematopoietic stem cells through stepwise fating events. To characterize gene expression programs driving lineage choice, we sequenced RNA from eight primary human hematopoietic progenitor populations representing the major myeloid commitment stages and the main lymphoid stage. We identified extensive cell type-specific expression changes: 6711 genes and 10,724 transcripts, enriched in non-protein-coding elements at early stages of differentiation. In addition, we found 7881 novel splice junctions and 2301 differentially used alternative splicing events, enriched in genes involved in regulatory processes. We demonstrated experimentally cell-specific isoform usage, identifying nuclear factor I/B (NFIB) as a regulator of megakaryocyte maturation-the platelet precursor. Our data highlight the complexity of fating events in closely related progenitor populations, the understanding of which is essential for the advancement of transplantation and regenerative medicine.

A vision and strategy for the virtual physiological human: 2012 update

European funding under Framework 7 (FP7) for the virtual physiological human (VPH) project has been in place now for 5 years. The VPH Network of Excellence (NoE) has been set up to help develop common standards, open source software, freely accessible data and model repositories, and various training and dissemination activities for the project. It is also working to coordinate the many clinically targeted projects that have been funded under the FP7 calls. An initial vision for the VPH was defined by the FP6 STEP project in 2006. In 2010, we wrote an assessment of the accomplishments of the first two years of the VPH in which we considered the biomedical science, healthcare and information and communications technology challenges facing the project (Hunter et al. 2010 Phil. Trans. R. Soc. A 368, 2595-2614 (doi:10.1098/rsta.2010.0048)). We proposed that a not-for-profit professional umbrella organization, the VPH Institute, should be established as a means of sustaining the VPH vision beyond the time-frame of the NoE. Here, we update and extend this assessment and in particular address the following issues raised in response to Hunter et al.: (i) a vision for the VPH updated in the light of progress made so far, (ii) biomedical science and healthcare challenges that the VPH initiative can address while also providing innovation opportunities for the European industry, and (iii) external changes needed in regulatory policy and business models to realize the full potential that the VPH has to offer to industry, clinics and society generally.

HuPSON: the human physiology simulation ontology

BACKGROUND

Large biomedical simulation initiatives, such as the Virtual Physiological Human (VPH), are substantially dependent on controlled vocabularies to facilitate the exchange of information, of data and of models. Hindering these initiatives is a lack of a comprehensive ontology that covers the essential concepts of the simulation domain.

RESULTS

We propose a first version of a newly constructed ontology, HuPSON, as a basis for shared semantics and interoperability of simulations, of models, of algorithms and of other resources in this domain. The ontology is based on the Basic Formal Ontology, and adheres to the MIREOT principles; the constructed ontology has been evaluated via structural features, competency questions and use case scenarios.The ontology is freely available at: http://www.scai.fraunhofer.de/en/business-research-areas/bioinformatics/downloads.html (owl files) and http://bishop.scai.fraunhofer.de/scaiview/ (browser).

CONCLUSIONS

HuPSON provides a framework for a) annotating simulation experiments, b) retrieving relevant information that are required for modelling, c) enabling interoperability of algorithmic approaches used in biomedical simulation, d) comparing simulation results and e) linking knowledge-based approaches to simulation-based approaches. It is meant to foster a more rapid uptake of semantic technologies in the modelling and simulation domain, with particular focus on the VPH domain.

Functional tissue units and their primary tissue motifs in multi-scale physiology

Background

Histology information management relies on complex knowledge derived from morphological tissue analyses. These approaches have not significantly facilitated the general integration of tissue- and molecular-level knowledge across the board in support of a systematic classification of tissue function, as well as the coherent multi-scale study of physiology. Our work aims to support directly these integrative goals.

Results

We describe, for the first time, the precise biophysical and topological characteristics of functional units of tissue. Such a unit consists of a three-dimensional block of cells centred around a capillary, such that each cell in this block is within diffusion distance from any other cell in the same block. We refer to this block as a functional tissue unit. As a means of simplifying the knowledge representation of this unit, and rendering this knowledge more amenable to automated reasoning and classification, we developed a simple descriptor of its cellular content and anatomical location, which we refer to as a primary tissue motif. In particular, a primary motif captures the set of cellular participants of diffusion-mediated interactions brokered by secreted products to create a tissue-level molecular network.

Conclusions

Multi-organ communication, therefore, may be interpreted in terms of interactions between molecular networks housed by interconnected functional tissue units. By extension, a functional picture of an organ, or its tissue components, may be rationally assembled using a collection of these functional tissue units as building blocks. In our work, we outline the biophysical rationale for a rigorous definition of a unit of functional tissue organization, and demonstrate the application of primary motifs in tissue classification. In so doing, we acknowledge (i) the fundamental role of capillaries in directing and radically informing tissue architecture, as well as (ii) the importance of taking into full account the critical influence of neighbouring cellular environments when studying complex developmental and pathological phenomena.

Eliciting candidate anatomical routes for protein interactions: a scenario from endocrine physiology

Background

In this paper, we use: i) formalised anatomical knowledge of connectivity between body structures and ii) a formal theory of physiological transport between fluid compartments in order to define and make explicit the routes followed by proteins to a site of interaction. The underlying processes are the objects of mathematical models of physiology and, therefore, the motivation for the approach can be understood as using knowledge representation and reasoning methods to propose concrete candidate routes corresponding to correlations between variables in mathematical models of physiology. In so doing, the approach projects physiology models onto a representation of the anatomical and physiological reality which underpins them.

Results

The paper presents a method based on knowledge representation and reasoning for eliciting physiological communication routes. In doing so, the paper presents the core knowledge representation and algorithms using it in the application of the method. These are illustrated through the description of a prototype implementation and the treatment of a simple endocrine scenario whereby a candidate route of communication between ANP and its receptors on the external membrane of smooth muscle cells in renal arterioles is elicited. The potential of further development of the approach is illustrated through the informal discussion of a more complex scenario.

Conclusions

The work presented in this paper supports research in intercellular communication by enabling knowledge‐based inference on physiologically‐related biomedical data and models.

Integrating knowledge representation and quantitative modelling in physiology

A wealth of potentially shareable resources, such as data and models, is being generated through the study of physiology by computational means. Although in principle the resources generated are reusable, in practice, few can currently be shared. A key reason for this disparity stems from the lack of consistent cataloguing and annotation of these resources in a standardised manner. Here, we outline our vision for applying community-based modelling standards in support of an automated integration of models across physiological systems and scales. Two key initiatives, the Physiome Project and the European contribution - the Virtual Phsysiological Human Project, have emerged to support this multiscale model integration, and we focus on the role played by two key components of these frameworks, model encoding and semantic metadata annotation. We present examples of biomedical modelling scenarios (the endocrine effect of atrial natriuretic peptide, and the implications of alcohol and glucose toxicity) to illustrate the role that encoding standards and knowledge representation approaches, such as ontologies, could play in the management, searching and visualisation of physiology models, and thus in providing a rational basis for healthcare decisions and contributing towards realising the goal of of personalized medicine.

An infrastructure for ontology-based information systems in biomedicine: RICORDO case study

SUMMARY

The article presents an infrastructure for supporting the semantic interoperability of biomedical resources based on the management (storing and inference-based querying) of their ontology-based annotations. This infrastructure consists of: (i) a repository to store and query ontology-based annotations; (ii) a knowledge base server with an inference engine to support the storage of and reasoning over ontologies used in the annotation of resources; (iii) a set of applications and services allowing interaction with the integrated repository and knowledge base. The infrastructure is being prototyped and developed and evaluated by the RICORDO project in support of the knowledge management of biomedical resources, including physiology and pharmacology models and associated clinical data.

AVAILABILITY AND IMPLEMENTATION

The RICORDO toolkit and its source code are freely available from http://ricordo.eu/relevant-resources.

CONTACT

sarala@ebi.ac.uk.

The RICORDO approach to semantic interoperability for biomedical data and models: strategy, standards and solutions

Background

The practice and research of medicine generates considerable quantities of data and model resources (DMRs). Although in principle biomedical resources are re-usable, in practice few can currently be shared. In particular, the clinical communities in physiology and pharmacology research, as well as medical education, (i.e. PPME communities) are facing considerable operational and technical obstacles in sharing data and models.

Findings

We outline the efforts of the PPME communities to achieve automated semantic interoperability for clinical resource documentation in collaboration with the RICORDO project. Current community practices in resource documentation and knowledge management are overviewed. Furthermore, requirements and improvements sought by the PPME communities to current documentation practices are discussed. The RICORDO plan and effort in creating a representational framework and associated open software toolkit for the automated management of PPME metadata resources is also described.

Conclusions

RICORDO is providing the PPME community with tools to effect, share and reason over clinical resource annotations. This work is contributing to the semantic interoperability of DMRs through ontology-based annotation by (i) supporting more effective navigation and re-use of clinical DMRs, as well as (ii) sustaining interoperability operations based on the criterion of biological similarity. Operations facilitated by RICORDO will range from automated dataset matching to model merging and managing complex simulation workflows. In effect, RICORDO is contributing to community standards for resource sharing and interoperability.

Integrating systems biology models and biomedical ontologies

BACKGROUND

Systems biology is an approach to biology that emphasizes the structure and dynamic behavior of biological systems and the interactions that occur within them. To succeed, systems biology crucially depends on the accessibility and integration of data across domains and levels of granularity. Biomedical ontologies were developed to facilitate such an integration of data and are often used to annotate biosimulation models in systems biology.

RESULTS

We provide a framework to integrate representations of in silico systems biology with those of in vivo biology as described by biomedical ontologies and demonstrate this framework using the Systems Biology Markup Language. We developed the SBML Harvester software that automatically converts annotated SBML models into OWL and we apply our software to those biosimulation models that are contained in the BioModels Database. We utilize the resulting knowledge base for complex biological queries that can bridge levels of granularity, verify models based on the biological phenomenon they represent and provide a means to establish a basic qualitative layer on which to express the semantics of biosimulation models.

CONCLUSIONS

We establish an information flow between biomedical ontologies and biosimulation models and we demonstrate that the integration of annotated biosimulation models and biomedical ontologies enables the verification of models as well as expressive queries. Establishing a bi-directional information flow between systems biology and biomedical ontologies has the potential to enable large-scale analyses of biological systems that span levels of granularity from molecules to organisms.

A vision and strategy for the virtual physiological human in 2010 and beyond

European funding under framework 7 (FP7) for the virtual physiological human (VPH) project has been in place now for nearly 2 years. The VPH network of excellence (NoE) is helping in the development of common standards, open-source software, freely accessible data and model repositories, and various training and dissemination activities for the project. It is also helping to coordinate the many clinically targeted projects that have been funded under the FP7 calls. An initial vision for the VPH was defined by framework 6 strategy for a European physiome (STEP) project in 2006. It is now time to assess the accomplishments of the last 2 years and update the STEP vision for the VPH. We consider the biomedical science, healthcare and information and communications technology challenges facing the project and we propose the VPH Institute as a means of sustaining the vision of VPH beyond the time frame of the NoE.

Reactome knowledgebase of human biological pathways and processes

Reactome (http://www.reactome.org) is an expert-authored, peer-reviewed knowledgebase of human reactions and pathways that functions as a data mining resource and electronic textbook. Its current release includes 2975 human proteins, 2907 reactions and 4455 literature citations. A new entity-level pathway viewer and improved search and data mining tools facilitate searching and visualizing pathway data and the analysis of user-supplied high-throughput data sets. Reactome has increased its utility to the model organism communities with improved orthology prediction methods allowing pathway inference for 22 species and through collaborations to create manually curated Reactome pathway datasets for species including Arabidopsis, Oryza sativa (rice), Drosophila and Gallus gallus (chicken). Reactome's data content and software can all be freely used and redistributed under open source terms.

SIGLEC16 encodes a DAP12-associated receptor expressed in macrophages that evolved from its inhibitory counterpart SIGLEC11 and has functional and non-functional alleles in humans

Sialic acid binding immunoglobulin-like lectins (Siglec) are important components of immune recognition. The organization of Siglec genes in different species is consistent with rapid selection imposed by pathogens. We studied SIGLEC11 genes in human, rodent, dog, cow and non-human primates. The lineages of SIGLEC11 genes in these species have undergone dynamic gene duplication and conversion, forming a potential inhibitory (SIGLEC11)/activating (SIGLEC16) receptor pair in chimpanzee and humans. A cDNA encoding human Siglec-16, currently classed as a pseudogene in the databases (SIGLECP16), is expressed in various cell lines and tissues. A polymorphism screen for the two alleles (wild type and four-base pair deletion, 4bpDelta) of SIGLEC16 found their frequencies to be 50% amongst the UK population. A search for donor sequences for SIGLEC16 revealed a subfamily of activating Siglec with charged transmembrane domains predicted to associate with ITAM-encoding adaptor proteins. In support of this, Siglec-16 was expressed at the cell surface in the presence of DAP12, but not the FcRgamma chain. Using antisera specific to the cytoplasmic tail of Siglec-16, we identified Siglec-16 expression in CD14(+) tissue macrophages and in normal human brain, cancerous oesophagus and lung. This is the first activating human Siglec receptor found to have functional and non-functional alleles within the population.

Reactome: a knowledge base of biologic pathways and processes

Reactome, an online curated resource for human pathway data, can be used to infer equivalent reactions in non-human species and as a tool to aid in the interpretation of microarrays and other high-throughput data sets.

Reactome http://www.reactome.org, an online curated resource for human pathway data, provides infrastructure for computation across the biologic reaction network. We use Reactome to infer equivalent reactions in multiple nonhuman species, and present data on the reliability of these inferred reactions for the distantly related eukaryote Saccharomyces cerevisiae. Finally, we describe the use of Reactome both as a learning resource and as a computational tool to aid in the interpretation of microarrays and similar large-scale datasets.

Characterization of the opossum immune genome provides insights into the evolution of the mammalian immune system

The availability of the first marsupial genome sequence has allowed us to characterize the immunome of the gray short-tailed opossum (Monodelphis domestica). Here we report the identification of key immune genes, including the highly divergent chemokines, defensins, cathelicidins, and Natural Killer cell receptors. It appears that the increase in complexity of the mammalian immune system occurred prior to the divergence of the marsupial and eutherian lineages approximately 180 million years ago. Genomes of ancestral mammals most likely contained all of the key mammalian immune gene families, with evolution on different continents, in the presence of different pathogens leading to lineage specific expansions and contractions, resulting in some minor differences in gene number and composition between different mammalian lineages. Gene expansion and extensive heterogeneity in opossum antimicrobial peptide genes may have evolved as a consequence of the newborn young needing to survive without an adaptive immune system in a pathogen laden environment. Given the similarities in the genomic architecture of the marsupial and eutherian immune systems, we propose that marsupials are ideal model organisms for the study of developmental immunology.

Relationship between SPRY and B30.2 protein domains. Evolution of a component of immune defence?

SPRY and B30.2 are homologous domains which can be identified in 11 protein families encoded in the human genome. These include cell surface receptors of the immunoglobulin super-family (BTNs), negative regulators of the JAK/STAT pathway (SOCS-box SSB1-4) and proteins encoded by the numerous TRIM genes. Collectively, proteins containing SPRY and B30.2 domains cover a wide range of functions, including regulation of cytokine signalling (SOCS), RNA metabolism (DDX1, hnRNPs), intracellular calcium release (RyR receptors), immunity to retroviruses (TRIM5alpha) as well as regulatory and developmental processes (HERC1, Ash2L). In order to clarify the evolutionary relationship between the two domains, we compiled a curated database of SPRY and B30.2-domain sequences. We show that while SPRY domains are evolutionarily ancient, B30.2 domains, found in BTN and TRIM proteins, are a more recent evolutionary adaptation, comprising the combination of SPRY with an additional domain, PRY. The combination of SPRY and PRY to produce B30.2 domains may have been selected and maintained as a component of immune defence.

IRIS: A database surveying known human immune system genes

We have compiled an online database of known human defense genes: the Immunogenetic Related Information Source (IRIS). As of October 1, 2004, there are 1562 immune genes recorded in IRIS, representing 7% of the human genome. This resource contains searchable information including chromosomal location, sequence data, and a curated functional annotation for each entry. We used IRIS as a basis for analyzing the composition and characteristics of the immune genome, such as gene clustering, polymorphism, and relationship to disease. High protein sequence similarity correlated inversely with distance between immune genes, consistent with clustering of duplicated loci. We also found that, even though some immune genes exhibit high levels of polymorphism, such as MHC class I, the range of levels of polymorphism in immune genes is similar to that of nonimmune genes. Approximately 20% of immune genes have a known disease association. IRIS is available online at .

VH gene segments in the mouse and human genomes

We have examined the mouse genome sequence to determine its VH gene segment repertoire. In all, 141 segments are mapped to a 3 Mb region of chromosome 12. There is evidence that 92 of these are functional in the mouse strain used for the genome sequence, C57BL/6J; 12 are functional in other mouse strains, and 37 are pseudogenes. The mouse VH gene segment repertoire is therefore twice the size of that in humans. The mouse and human loci bear no large-scale similarity to each other. The 104 functional segments belong to one of the 15 known sequence subgroups, which have been further clustered into eight sets here. Seven of these sets, comprising 101 sequences, are related to five of the human VH families and have the same canonical structures in their hypervariable regions. Duplication of members of one set in the distal half of the locus is mainly responsible for the larger size of the mouse repertoire. Phylogenetic analysis of the VH segments indicates that most of the sequences in the human and mouse VH loci have arisen subsequent to the divergence of the two organisms from their common ancestor.

Exegesis: a procedure to improve gene predictions and its use to find immunoglobulin superfamily proteins in the human and mouse genomes

Exegesis is a procedure to refine the gene predictions that are produced for complex genomes, e.g. those of humans and mice. It uses the program Genewise, sequences determined by experiment, experimental maps of gene segment libraries and a new browser that allows the user to rapidly inspect and compare multiple gene maps to regions of genomic sequences. The procedure should be of general use. Here, we use the procedure to find members of the immunoglobulin superfamily in the human and mouse genomes. To do this, Exegesis was used to process the original gene predictions from the automated Ensembl annotation pipeline. Exegesis produced (i) many more complete genes and new transcripts and (ii) a mapping of the immunoglobulin and T cell receptor gene libraries to the genome, which are largely absent in the Ensembl set.

Exploring the immunogenome with bioinformatics

A better description of the immune system can be afforded if the latest developments in bioinformatics are applied to integrate sequence with structure and function. Clear guidelines for the upgrade of the bioinformatic capability of the immunogenetics laboratory are discussed in the light of more powerful methods to detect homology, combined approaches to predict the three dimensional properties of a protein and a robust strategy to represent the biological role of a gene.