A multi-omics systems vaccinology resource to develop and test computational models of immunity

Systems vaccinology studies have identified factors affecting individual vaccine responses, but comparing these findings is challenging due to varying study designs. To address this lack of reproducibility, we established a community resource for comparing Bordetella pertussis booster responses and to host annual contests for predicting patients' vaccination outcomes. We report here on our experiences with the "dry-run" prediction contest. We found that, among 20+ models adopted from the literature, the most successful model predicting vaccination outcome was based on age alone. This confirms our concerns about the reproducibility of conclusions between different vaccinology studies. Further, we found that, for newly trained models, handling of baseline information on the target variables was crucial. Overall, multiple co-inertia analysis gave the best results of the tested modeling approaches. Our goal is to engage community in these prediction challenges by making data and models available and opening a public contest in August 2024.

A systems vaccinology resource to develop and test computational models of immunity

Computational models that predict an individual's response to a vaccine offer the potential for mechanistic insights and personalized vaccination strategies. These models are increasingly derived from systems vaccinology studies that generate immune profiles from human cohorts pre- and post-vaccination. Most of these studies involve relatively small cohorts and profile the response to a single vaccine. The ability to assess the performance of the resulting models would be improved by comparing their performance on independent datasets, as has been done with great success in other areas of biology such as protein structure predictions. To transfer this approach to system vaccinology studies, we established a prototype platform that focuses on the evaluation of Computational Models of Immunity to Pertussis Booster vaccinations (CMI-PB). A community resource, CMI-PB generates experimental data for the explicit purpose of model evaluation, which is performed through a series of annual data releases and associated contests. We here report on our experience with the first such 'dry run' for a contest where the goal was to predict individual immune responses based on pre-vaccination multi-omic profiles. Over 30 models adopted from the literature were tested, but only one was predictive, and was based on age alone. The performance of new models built using CMI-PB training data was much better, but varied significantly based on the choice of pre-vaccination features used and the model building strategy. This suggests that previously published models developed for other vaccines do not generalize well to Pertussis Booster vaccination. Overall, these results reinforced the need for comparative analysis across models and datasets that CMI-PB aims to achieve. We are seeking wider community engagement for our first public prediction contest, which will open in early 2024.

Multi-omic longitudinal study reveals immune correlates of clinical course among hospitalized COVID-19 patients

The IMPACC cohort, composed of >1,000 hospitalized COVID-19 participants, contains five illness trajectory groups (TGs) during acute infection (first 28 days), ranging from milder (TG1-3) to more severe disease course (TG4) and death (TG5). Here, we report deep immunophenotyping, profiling of >15,000 longitudinal blood and nasal samples from 540 participants of the IMPACC cohort, using 14 distinct assays. These unbiased analyses identify cellular and molecular signatures present within 72 h of hospital admission that distinguish moderate from severe and fatal COVID-19 disease. Importantly, cellular and molecular states also distinguish participants with more severe disease that recover or stabilize within 28 days from those that progress to fatal outcomes (TG4 vs. TG5). Furthermore, our longitudinal design reveals that these biologic states display distinct temporal patterns associated with clinical outcomes. Characterizing host immune responses in relation to heterogeneity in disease course may inform clinical prognosis and opportunities for intervention.

Coronavirus Immunotherapeutic Consortium Database

The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has seen multiple anti-SARS-CoV-2 antibodies being generated globally. It is difficult, however, to assemble a useful compendium of these biological properties if they are derived from experimental measurements performed at different sites under different experimental conditions. The Coronavirus Immunotherapeutic Consortium (COVIC) circumvents these issues by experimentally testing blinded antibodies side by side for several functional activities. To collect these data in a consistent fashion and make it publicly available, we established the COVIC database (COVIC-DB, https://covicdb.lji.org/). This database enables systematic analysis and interpretation of this large-scale dataset by providing a comprehensive view of various features such as affinity, neutralization, in vivo protection and effector functions for each antibody. Interactive graphs enable direct comparisons of antibodies based on select functional properties. We demonstrate how the COVIC-DB can be utilized to examine relationships among antibody features, thereby guiding the design of therapeutic antibody cocktails. Database URL  https://covicdb.lji.org/.

Ontology Development Kit: a toolkit for building, maintaining and standardizing biomedical ontologies

Similar to managing software packages, managing the ontology life cycle involves multiple complex workflows such as preparing releases, continuous quality control checking and dependency management. To manage these processes, a diverse set of tools is required, from command-line utilities to powerful ontology-engineering environmentsr. Particularly in the biomedical domain, which has developed a set of highly diverse yet inter-dependent ontologies, standardizing release practices and metadata and establishing shared quality standards are crucial to enable interoperability. The Ontology Development Kit (ODK) provides a set of standardized, customizable and automatically executable workflows, and packages all required tooling in a single Docker image. In this paper, we provide an overview of how the ODK works, show how it is used in practice and describe how we envision it driving standardization efforts in our community. Database URL: https://github.com/INCATools/ontology-development-kit.

Phenotypes of disease severity in a cohort of hospitalized COVID-19 patients: Results from the IMPACC study

BACKGROUND

Better understanding of the association between characteristics of patients hospitalized with coronavirus disease 2019 (COVID-19) and outcome is needed to further improve upon patient management.

METHODS

Immunophenotyping Assessment in a COVID-19 Cohort (IMPACC) is a prospective, observational study of 1164 patients from 20 hospitals across the United States. Disease severity was assessed using a 7-point ordinal scale based on degree of respiratory illness. Patients were prospectively surveyed for 1 year after discharge for post-acute sequalae of COVID-19 (PASC) through quarterly surveys. Demographics, comorbidities, radiographic findings, clinical laboratory values, SARS-CoV-2 PCR and serology were captured over a 28-day period. Multivariable logistic regression was performed.

FINDINGS

The median age was 59 years (interquartile range [IQR] 20); 711 (61%) were men; overall mortality was 14%, and 228 (20%) required invasive mechanical ventilation. Unsupervised clustering of ordinal score over time revealed distinct disease course trajectories. Risk factors associated with prolonged hospitalization or death by day 28 included age ≥ 65 years (odds ratio [OR], 2.01; 95% CI 1.28-3.17), Hispanic ethnicity (OR, 1.71; 95% CI 1.13-2.57), elevated baseline creatinine (OR 2.80; 95% CI 1.63- 4.80) or troponin (OR 1.89; 95% 1.03-3.47), baseline lymphopenia (OR 2.19; 95% CI 1.61-2.97), presence of infiltrate by chest imaging (OR 3.16; 95% CI 1.96-5.10), and high SARS-CoV2 viral load (OR 1.53; 95% CI 1.17-2.00). Fatal cases had the lowest ratio of SARS-CoV-2 antibody to viral load levels compared to other trajectories over time (p=0.001). 589 survivors (51%) completed at least one survey at follow-up with 305 (52%) having at least one symptom consistent with PASC, most commonly dyspnea (56% among symptomatic patients). Female sex was the only associated risk factor for PASC.

INTERPRETATION

Integration of PCR cycle threshold, and antibody values with demographics, comorbidities, and laboratory/radiographic findings identified risk factors for 28-day outcome severity, though only female sex was associated with PASC. Longitudinal clinical phenotyping offers important insights, and provides a framework for immunophenotyping for acute and long COVID-19.

FUNDING

NIH.

A Simple Standard for Sharing Ontological Mappings (SSSOM)

Despite progress in the development of standards for describing and exchanging scientific information, the lack of easy-to-use standards for mapping between different representations of the same or similar objects in different databases poses a major impediment to data integration and interoperability. Mappings often lack the metadata needed to be correctly interpreted and applied. For example, are two terms equivalent or merely related? Are they narrow or broad matches? Or are they associated in some other way? Such relationships between the mapped terms are often not documented, which leads to incorrect assumptions and makes them hard to use in scenarios that require a high degree of precision (such as diagnostics or risk prediction). Furthermore, the lack of descriptions of how mappings were done makes it hard to combine and reconcile mappings, particularly curated and automated ones. We have developed the Simple Standard for Sharing Ontological Mappings (SSSOM) which addresses these problems by: (i) Introducing a machine-readable and extensible vocabulary to describe metadata that makes imprecision, inaccuracy and incompleteness in mappings explicit. (ii) Defining an easy-to-use simple table-based format that can be integrated into existing data science pipelines without the need to parse or query ontologies, and that integrates seamlessly with Linked Data principles. (iii) Implementing open and community-driven collaborative workflows that are designed to evolve the standard continuously to address changing requirements and mapping practices. (iv) Providing reference tools and software libraries for working with the standard. In this paper, we present the SSSOM standard, describe several use cases in detail and survey some of the existing work on standardizing the exchange of mappings, with the goal of making mappings Findable, Accessible, Interoperable and Reusable (FAIR). The SSSOM specification can be found at http://w3id.org/sssom/spec. Database URL: http://w3id.org/sssom/spec.

The Minimal Information about MHC Multimers (MIAMM)

The Minimal Information about MHC Multimers (MIAMM, miamm.lji.org) is a recently established data standard to be applied to publications utilizing these reagents. Available at miamm.lji.org, we explain how to easily represent multimer reagents in a standardized format using ontology terminology. Additionally, we provide a free, publicly available Multimer Validation Tool. This tool helps users adopt this new data standard and was proven to be generally applicable to real life use cases by its validation of the data present in the NIH Tetramer Core Facility and the nearly 18,500 multimer assays in the Immune Epitope Database (IEDB). As the scientific public adopts MIAMM, the quality, reproducibility, and annotatability of MHC multimer reagent data in the scientific literature will be improved.

Funding: JDA, RAW, and DLL acknowledge support from the contract for the NIH Tetramer Facility (75N93020D00005) from the Yerkes National Primate Research Center (P51OD011132), and the Emory Center for AIDS Research (P30AI050409). RV, JAO, AM, and BP acknowledge support from National Institutes of Health grant R24 HG010032. RV, JAO, AM, BP, and AS acknowledge support from National Institutes of Health contract 75N93019C00001

Minimal Information about MHC Multimers (MIAMM)

With the goal of improving the reproducibility and annotatability of MHC multimer reagent data, we present the establishment of a new data standard: Minimal Information about MHC Multimers (https://miamm.lji.org/). Multimers are engineered reagents composed of a ligand and a MHC, which can be represented in a standardized format using ontology terminology. We provide an online Web site to host the details of the standard, as well as a validation tool to assist with the adoption of the standard. We hope that this publication will bring increased awareness of Minimal Information about MHC Multimers and drive acceptance, ultimately improving the quality and documentation of multimer data in the scientific literature.

OBO Foundry in 2021: operationalizing open data principles to evaluate ontologies

Biological ontologies are used to organize, curate and interpret the vast quantities of data arising from biological experiments. While this works well when using a single ontology, integrating multiple ontologies can be problematic, as they are developed independently, which can lead to incompatibilities. The Open Biological and Biomedical Ontologies (OBO) Foundry was created to address this by facilitating the development, harmonization, application and sharing of ontologies, guided by a set of overarching principles. One challenge in reaching these goals was that the OBO principles were not originally encoded in a precise fashion, and interpretation was subjective. Here, we show how we have addressed this by formally encoding the OBO principles as operational rules and implementing a suite of automated validation checks and a dashboard for objectively evaluating each ontology’s compliance with each principle. This entailed a substantial effort to curate metadata across all ontologies and to coordinate with individual stakeholders. We have applied these checks across the full OBO suite of ontologies, revealing areas where individual ontologies require changes to conform to our principles. Our work demonstrates how a sizable, federated community can be organized and evaluated on objective criteria that help improve overall quality and interoperability, which is vital for the sustenance of the OBO project and towards the overall goals of making data Findable, Accessible, Interoperable, and Reusable (FAIR).

Database URL http://obofoundry.org/

Standardization of assay representation in the Ontology for Biomedical Investigations

The Ontology for Biomedical Investigations (OBI) underwent a focused review of assay term annotations, logic and hierarchy with a goal to improve and standardize these terms. As a result, inconsistencies in W3C Web Ontology Language (OWL) expressions were identified and corrected, and additionally, standardized design patterns and a formalized template to maintain them were developed. We describe here this informative and productive process to describe the specific benefits and obstacles for OBI and the universal lessons for similar projects.

Computational models of Immunity – Pertussis Boost (CMI-PB): Engaging the broader scientific community to develop predictive models of Tdap booster vaccination

Whooping cough is a contagious disease caused by Bordetella Pertussis. The introduction of an inactivated whole bacteria vaccine (wP) in the 1940s led to a dramatic decrease in cases. However, due to vaccine related side-effects, this was substituted by the acellular vaccine (aP) in the 90’s which resulted in rise in cases. In order to determine if there are differences between those primed with aP vs. wP in infancy, we created a model using longitudinal samples from aP boosted individuals as a proxy for antigen encounter in vivo. In previous research, we observed substantial variability in magnitude of vaccine-induced responses between individuals regardless of their priming. Yet, we identified a systematic increase of Th2 polarization of T cells at day 7, a higher expression of CCL3 in PBMC on day 3 post-boost, and an increase of IgG4 antibody polarization in aP individuals. It is not clear how these different observations are interlinked.

We hope to address this question in our project, Computational Models of Immunity – Pertussis Boost (CMI-PB). We are establishing a website that will release omics data (10 aP vs 10 wP infancy primed donors) and engage students with educational materials, and help organize a yearly contest with the broader scientific community to help develop predictive models of immunity. This study will identify the key factors responsible for the differences between aP and wP primed individuals, while also providing a model for general vaccinology.

An immunologically friendly classification of non-peptidic ligands

The Immune Epitope Database (IEDB) freely provides experimental data regarding immune epitopes to the scientific public. The main users of the IEDB are immunologists who can easily use our web interface to search for peptidic epitopes via their simple single-letter codes. For example, 'A' stands for 'alanine'. Similarly, users can easily navigate the IEDB's simplified NCBI taxonomy hierarchy to locate proteins from specific organisms. However, some epitopes are non-peptidic, such as carbohydrates, lipids, chemicals and drugs, and it is more challenging to consistently name them and search upon, making access to their data more problematic for immunologists. Therefore, we set out to improve access to non-peptidic epitope data in the IEDB through the simplification of the non-peptidic hierarchy used in our search interfaces. Here, we present these efforts and their outcomes. Database URL:  http://www.iedb.org/.

The Immune Epitope Database (IEDB): 2018 update

The Immune Epitope Database (IEDB, iedb.org) captures experimental data confined in figures, text and tables of the scientific literature, making it freely available and easily searchable to the public. The scope of the IEDB extends across immune epitope data related to all species studied and includes antibody, T cell, and MHC binding contexts associated with infectious, allergic, autoimmune, and transplant related diseases. Having been publicly accessible for >10 years, the recent focus of the IEDB has been improved query and reporting functionality to meet the needs of our users to access and summarize data that continues to grow in quantity and complexity. Here we present an update on our current efforts and future goals.

A structured model for immune exposures

An Immune Exposure is the process by which components of the immune system first encounter a potential trigger. The ability to describe consistently the details of the Immune Exposure process was needed for data resources responsible for housing scientific data related to the immune response. This need was met through the development of a structured model for Immune Exposures. This model was created during curation of the immunology literature, resulting in a robust model capable of meeting the requirements of such data. We present this model with the hope that overlapping projects will adopt and or contribute to this work.

ROBOT: A Tool for Automating Ontology Workflows

Background

Ontologies are invaluable in the life sciences, but building and maintaining ontologies often requires a challenging number of distinct tasks such as running automated reasoners and quality control checks, extracting dependencies and application-specific subsets, generating standard reports, and generating release files in multiple formats. Similar to more general software development, automation is the key to executing and managing these tasks effectively and to releasing more robust products in standard forms.

For ontologies using the Web Ontology Language (OWL), the OWL API Java library is the foundation for a range of software tools, including the Protégé ontology editor. In the Open Biological and Biomedical Ontologies (OBO) community, we recognized the need to package a wide range of low-level OWL API functionality into a library of common higher-level operations and to make those operations available as a command-line tool.

Results

ROBOT (a recursive acronym for “ROBOT is an OBO Tool”) is an open source library and command-line tool for automating ontology development tasks. The library can be called from any programming language that runs on the Java Virtual Machine (JVM). Most usage is through the command-line tool, which runs on macOS, Linux, and Windows. ROBOT provides ontology processing commands for a variety of tasks, including commands for converting formats, running a reasoner, creating import modules, running reports, and various other tasks. These commands can be combined into larger workflows using a separate task execution system such as GNU Make, and workflows can be automatically executed within continuous integration systems.

Conclusions

ROBOT supports automation of a wide range of ontology development tasks, focusing on OBO conventions. It packages common high-level ontology development functionality into a convenient library, and makes it easy to configure, combine, and execute individual tasks in comprehensive, automated workflows. This helps ontology developers to efficiently create, maintain, and release high-quality ontologies, so that they can spend more time focusing on development tasks. It also helps guarantee that released ontologies are free of certain types of logical errors and conform to standard quality control checks, increasing the overall robustness and efficiency of the ontology development lifecycle.

Formal representation of immunology related data with ontologies

The Human Immunology Project Consortium (HIPC) is a multicenter collaboration between research centers performing large-scale human immunology studies that focus on profiling the human immune response to natural infection and vaccination. “Immune exposures” are events such as natural infection and vaccination whereby the immune system may or may not respond to the exposure. Many of the HIPC studies investigate the response of specific cell populations after a variety of immune exposures. In order to cross-compare results from the many different centers and projects, we established a standardized representation of immune exposures and cell descriptions that simplifies data collection. By standardizing how this data is collected and stored, the vast amount of data collected by these diverse projects is made significantly more useful and interoperable. The data collected by the HIPC projects is stored in the National Institute of Health, Division of Allergy, Immunology and Transplantation funded resource, the Immunology Database and Analysis Portal (ImmPort). ImmPort was modified to provide the necessary structured data fields to capture our standardized representation of immune exposures and studied cell populations with a set of data fields that primarily utilize formal ontology terms. We will discuss the process of modeling immune exposures and cell populations via ontology terms, including real life scenarios from HIPC projects, as well as collaborations with existing ontology projects in order to meet the specific needs of immunologists.

The Immune Epitope Database enables and accelerates research

The Immune Epitope Database and Analysis Project (IEDB) is a freely available resource funded by the National Institute of Allergy and Infectious Diseases, to advance immunology research. The database allows easy searching of all published experimental data characterizing antibody and T cell epitopes studied in humans, non-human primates, and other animal species. Epitopes involved in infectious disease, allergy, autoimmunity, and transplant are included. The data were derived from more than 19,000 publications. The IEDB also hosts tools that assist in the prediction and analysis of B cell and T cell epitopes. In recent years, the IEDB has updated its search interface and added highly sought after data, such and antibody and TCR sequence information. We will detail how the IEDB can be used to facilitate immunological research.

Reporting and connecting cell type names and gating definitions through ontologies

Background

Human immunology studies often rely on the isolation and quantification of cell populations from an input sample based on flow cytometry and related techniques. Such techniques classify cells into populations based on the detection of a pattern of markers. The description of the cell populations targeted in such experiments typically have two complementary components: the description of the cell type targeted (e.g. ‘T cells’), and the description of the marker pattern utilized (e.g. CD14−, CD3+).

Results

We here describe our attempts to use ontologies to cross-compare cell types and marker patterns (also referred to as gating definitions). We used a large set of such gating definitions and corresponding cell types submitted by different investigators into ImmPort, a central database for immunology studies, to examine the ability to parse gating definitions using terms from the Protein Ontology (PRO) and cell type descriptions, using the Cell Ontology (CL). We then used logical axioms from CL to detect discrepancies between the two.

Conclusions

We suggest adoption of our proposed format for describing gating and cell type definitions to make comparisons easier. We also suggest a number of new terms to describe gating definitions in flow cytometry that are not based on molecular markers captured in PRO, but on forward- and side-scatter of light during data acquisition, which is more appropriate to capture in the Ontology for Biomedical Investigations (OBI). Finally, our approach results in suggestions on what logical axioms and new cell types could be considered for addition to the Cell Ontology.

FAIR principles and the IEDB: short-term improvements and a long-term vision of OBO-foundry mediated machine-actionable interoperability

The Immune Epitope Database (IEDB), at www.iedb.org, has the mission to make published experimental data relating to the recognition of immune epitopes easily available to the scientific public. By presenting curated data in a searchable database, we have liberated it from the tables and figures of journal articles, making it more accessible and usable by immunologists. Recently, the principles of Findability, Accessibility, Interoperability and Reusability have been formulated as goals that data repositories should meet to enhance the usefulness of their data holdings. We here examine how the IEDB complies with these principles and identify broad areas of success, but also areas for improvement. We describe short-term improvements to the IEDB that are being implemented now, as well as a long-term vision of true 'machine-actionable interoperability', which we believe will require community agreement on standardization of knowledge representation that can be built on top of the shared use of ontologies.

Identification of errors in the IEDB using ontologies

The Immune Epitope Database (IEDB) is a free online resource that has manually curated over 18 500 references from the scientific literature. Our database presents experimental data relating to the recognition of immune epitopes by the adaptive immune system in a structured, searchable manner. In order to be consistent and accurate in our data representation across many different journals, authors and curators, we have implemented several quality control measures, such as curation rules, controlled vocabularies and links to external ontologies and other resources. Ontologies and other resources have greatly benefited the IEDB through improved search interfaces, easier curation practices, interoperability between the IEDB and other databases and the identification of errors within our dataset. Here, we will elaborate on how ontology mapping and usage can be used to find and correct errors in a manually curated database.

Database URL: www.iedb.org

The eXtensible ontology development (XOD) principles and tool implementation to support ontology interoperability

Ontologies are critical to data/metadata and knowledge standardization, sharing, and analysis. With hundreds of biological and biomedical ontologies developed, it has become critical to ensure ontology interoperability and the usage of interoperable ontologies for standardized data representation and integration. The suite of web-based Ontoanimal tools (e.g., Ontofox, Ontorat, and Ontobee) support different aspects of extensible ontology development. By summarizing the common features of Ontoanimal and other similar tools, we identified and proposed an “eXtensible Ontology Development” (XOD) strategy and its associated four principles. These XOD principles reuse existing terms and semantic relations from reliable ontologies, develop and apply well-established ontology design patterns (ODPs), and involve community efforts to support new ontology development, promoting standardized and interoperable data and knowledge representation and integration. The adoption of the XOD strategy, together with robust XOD tool development, will greatly support ontology interoperability and robust ontology applications to support data to be Findable, Accessible, Interoperable and Reusable (i.e., FAIR).

Better living through ontologies at the Immune Epitope Database

The Immune Epitope Database (IEDB) project incorporates independently developed ontologies and controlled vocabularies into its curation and search interface. This simplifies curation practices, improves the user query experience and facilitates interoperability between the IEDB and other resources. While the use of independently developed ontologies has long been recommended as a best practice, there continues to be a significant number of projects that develop their own vocabularies instead, or that do not fully utilize the power of ontologies that they are using. We describe how we use ontologies in the IEDB, providing a concrete example of the benefits of ontologies in practice.

Database URL:www.iedb.org

Developing the Quantitative Histopathology Image Ontology (QHIO): A case study using the hot spot detection problem

Interoperability across data sets is a key challenge for quantitative histopathological imaging. There is a need for an ontology that can support effective merging of pathological image data with associated clinical and demographic data. To foster organized, cross-disciplinary, information-driven collaborations in the pathological imaging field, we propose to develop an ontology to represent imaging data and methods used in pathological imaging and analysis, and call it Quantitative Histopathological Imaging Ontology - QHIO. We apply QHIO to breast cancer hot-spot detection with the goal of enhancing reliability of detection by promoting the sharing of data between image analysts.

The Ontology for Biomedical Investigations

The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to existing databases, building data entry forms, and enabling interoperability between knowledge resources. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. Prior to OBI, it was not possible to use a single internally consistent resource that could be applied to multiple types of experiments for these applications. OBI has made this possible by creating terms for entities involved in biological and medical investigations and by importing parts of other biomedical ontologies such as GO, Chemical Entities of Biological Interest (ChEBI) and Phenotype Attribute and Trait Ontology (PATO) without altering their meaning. OBI is being used in a wide range of projects covering genomics, multi-omics, immunology, and catalogs of services. OBI has also spawned other ontologies (Information Artifact Ontology) and methods for importing parts of ontologies (Minimum information to reference an external ontology term (MIREOT)). The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions. The OBI Consortium maintains a web resource (http://obi-ontology.org) providing details on the people, policies, and issues being addressed in association with OBI. The current release of OBI is available at http://purl.obolibrary.org/obo/obi.owl.

Semantic representation of reported measurements in radiology

Background

In radiology, a vast amount of diverse data is generated, and unstructured reporting is standard. Hence, much useful information is trapped in free-text form, and often lost in translation and transmission. One relevant source of free-text data consists of reports covering the assessment of changes in tumor burden, which are needed for the evaluation of cancer treatment success. Any change of lesion size is a critical factor in follow-up examinations. It is difficult to retrieve specific information from unstructured reports and to compare them over time. Therefore, a prototype was implemented that demonstrates the structured representation of findings, allowing selective review in consecutive examinations and thus more efficient comparison over time.

Methods

We developed a semantic Model for Clinical Information (MCI) based on existing ontologies from the Open Biological and Biomedical Ontologies (OBO) library. MCI is used for the integrated representation of measured image findings and medical knowledge about the normal size of anatomical entities. An integrated view of the radiology findings is realized by a prototype implementation of a ReportViewer. Further, RECIST (Response Evaluation Criteria In Solid Tumors) guidelines are implemented by SPARQL queries on MCI. The evaluation is based on two data sets of German radiology reports: An oncologic data set consisting of 2584 reports on 377 lymphoma patients and a mixed data set consisting of 6007 reports on diverse medical and surgical patients. All measurement findings were automatically classified as abnormal/normal using formalized medical background knowledge, i.e., knowledge that has been encoded into an ontology. A radiologist evaluated 813 classifications as correct or incorrect. All unclassified findings were evaluated as incorrect.

Results

The proposed approach allows the automatic classification of findings with an accuracy of 96.4 % for oncologic reports and 92.9 % for mixed reports. The ReportViewer permits efficient comparison of measured findings from consecutive examinations. The implementation of RECIST guidelines with SPARQL enhances the quality of the selection and comparison of target lesions as well as the corresponding treatment response evaluation.

Conclusions

The developed MCI enables an accurate integrated representation of reported measurements and medical knowledge. Thus, measurements can be automatically classified and integrated in different decision processes. The structured representation is suitable for improved integration of clinical findings during decision-making. The proposed ReportViewer provides a longitudinal overview of the measurements.

An ontology for major histocompatibility restriction

BACKGROUND

MHC molecules are a highly diverse family of proteins that play a key role in cellular immune recognition. Over time, different techniques and terminologies have been developed to identify the specific type(s) of MHC molecule involved in a specific immune recognition context. No consistent nomenclature exists across different vertebrate species.

PURPOSE

To correctly represent MHC related data in The Immune Epitope Database (IEDB), we built upon a previously established MHC ontology and created an ontology to represent MHC molecules as they relate to immunological experiments.

DESCRIPTION

This ontology models MHC protein chains from 16 species, deals with different approaches used to identify MHC, such as direct sequencing verses serotyping, relates engineered MHC molecules to naturally occurring ones, connects genetic loci, alleles, protein chains and multi-chain proteins, and establishes evidence codes for MHC restriction. Where available, this work is based on existing ontologies from the OBO foundry.

CONCLUSIONS

Overall, representing MHC molecules provides a challenging and practically important test case for ontology building, and could serve as an example of how to integrate other ontology building efforts into web resources.

The immune epitope database (IEDB) 3.0

The IEDB, www.iedb.org, contains information on immune epitopes—the molecular targets of adaptive immune responses—curated from the published literature and submitted by National Institutes of Health funded epitope discovery efforts. From 2004 to 2012 the IEDB curation of journal articles published since 1960 has caught up to the present day, with >95% of relevant published literature manually curated amounting to more than 15 000 journal articles and more than 704 000 experiments to date. The revised curation target since 2012 has been to make recent research findings quickly available in the IEDB and thereby ensure that it continues to be an up-to-date resource. Having gathered a comprehensive dataset in the IEDB, a complete redesign of the query and reporting interface has been performed in the IEDB 3.0 release to improve how end users can access this information in an intuitive and biologically accurate manner. We here present this most recent release of the IEDB and describe the user testing procedures as well as the use of external ontologies that have enabled it.

Query enhancement through the practical application of ontology: the IEDB and OBI

Ontologies categorize entities, express relationships between them, and provide standardized definitions. Thus, they can be used to present and enforce the specific relationships between database components. The Immune Epitope Database (IEDB, http://www.iedb.org) utilizes the Ontology for Biomedical Investigations (OBI) and several additional ontologies to represent immune epitope mapping experiments. Here, we describe our experiences utilizing this representation in order to provide enhanced database search functionality. We applied a simple approach to incorporate the benefits of the information captured in a formal ontology directly into the user web interface, resulting in an improved user experience with minimal changes to the database itself. The integration is easy to maintain, provides standardized terms and definitions, and allows for subsumption queries. In addition to these immediate benefits, our long-term goal is to enable true semantic integration of data and knowledge in the biomedical domain. We describe our progress towards that goal and what we perceive as the main obstacles.

The fate of calcium in the diet of Rhodnius prolixus: storage in concretion bodies in the Malpighian tubules

We have investigated the fate of the large amounts of calcium ingested by Rhodnius prolixus in its meals of blood. 45Ca2+ injected into the haemolymph or fed to fifth-stage Rhodnius reared on rabbits is accumulated at high concentrations in the cells of the upper Malpighian tubules; very little is excreted from the body This 45Ca2+ accumulation goes on continuously for at least 12 days and the rate of uptake is increased several-fold within 3–4 days of a meal. The extent of calcium accumulation in tubule cells is correlated with the presence of intracellular membrane-bound concretion bodies, which are therefore likely sites of calcium deposition. X-ray diffraction showed that the calcium deposits are non-crystalline. Tubules from rabbit-fed fifth-stage Rhodnius contain 410 mmol l-1 calcium; in those from chicken-fed insects the calcium concentration is over 1 mol l-1; and in those fed in vitro on heparinised low-K+ sheep blood the calcium concentration is only 21 mmol l-1. The concentration of calcium in the haemolymph in all these insects was 8 mmol l-1 and its activity determined by an ion-selective electrode was 2.5 mmol l-1. 45Ca2+ deposited in the tubules is readily exchangeable, but the efflux preferentially passes to the haemolymph side of the tubule epithelium. The ability to sequester calcium in the Malpighian tubules may prevent calcium from interfering with reabsorptive processes in the rectum.

5-Hydroxytryptamine: a second diuretic hormone in Rhodnius prolixus

Bioassays of 5-hydroxytryptamine (5-HT) in fifth-instar Rhodnius prolixus haemolymph using Calliphora salivary glands indicate that: (1) biologically active 5-HT is present, (2) in unfed animals there is not enough 5-HT to stimulate Malpighian tubule fluid secretion, and (3) there is enough 5-HT soon after the initiation of feeding to stimulate rapid tubule secretion. The 5-HT receptor antagonists ketanserin and spiperone reversibly and selectively inhibit 5-HT-induced fluid secretion, indicating the presence of specific 5-HT receptors on Rhodnius Malpighian tubules. The data provide evidence that 5-HT is a naturally occurring hormone acting with a previously described peptide hormone to regulate diuresis in this species.

Action of activated 27,000 Mr toxin from Bacillus thuringiensis var. israelensis on Malpighian tubules of the insect, Rhodnius prolixus

The action of activated 27,000 Mr toxin from Bacillus thuringiensis var. israelensis (Bti toxin) on Malpighian tubules of Rhodnius prolixus has been investigated. Its binding to the tubules is slowed by low temperature but is not prevented even at 0 degree C. The binding is less effective at pH 10 than at pH7. Pretreatment of the tubules with 0.1 mmol l-1 ouabain or bumetanide or 1 mumol l-1 5-hydroxytryptamine did not affect the toxicity of the toxin. The toxin causes very large changes in the trans-epithelial potential difference; it changes from 40 mV, lumen negative, often to more than 100 mV, lumen positive. This reflects an initial collapse of the potential of the basal cell membrane, followed by a large positive-going potential change at the luminal cell membrane. Just prior to the effects of the toxin on rapid fluid secretion, the basal cell membrane becomes permeable to sucrose molecules. Raffinose at 170 mmol l-1 in the bathing solution does not protect the tubules from Bti toxin action but dextran, Mr5000, at 60 mmol l-1 significantly delayed failure of fluid secretion and, even more, the onset of staining of the tubule cells with Trypan Blue. Exposing tubules to saline that is calcium-free and/or magnesium-free, or has a composition adjusted to be similar to that of the intracellular milieu, does not affect the time course of failure of fluid secretion induced by the toxin. There is no evidence that effective aggregates of Bti toxin molecules are formed in concentrated solutions.(ABSTRACT TRUNCATED AT 250 WORDS)

Stimulation of sodium transport and fluid secretion by ouabain in an insect malpighian tubule

Ouabain, at all concentrations higher than 2 × 10(−7) mol l-1, stimulates the rate at which the Malpighian tubules of the insect, Rhodnius, transport sodium ions and fluid into the lumen. An effect on paracellular movement of sodium ions is unlikely because ouabain makes the electrical potential of the lumen more positive, which would slow diffusion of sodium into the lumen. Radioactive ouabain binds to the haemolymph-facing sides of the tubule cells but not to the luminal face. This binding is reduced in the presence of elevated levels of potassium or of non-radioactive ouabain. Bound ouabain is only slowly released on washing in ouabain-free saline. The evidence suggests that there is a Na+/K+-ATPase on the outer (serosal) membranes of the tubules. Such a pump would transport sodium in a direction opposed to the flow of ions and water involved in fluid transport; poisoning it with ouabain would remove this brake, and fluid flow and sodium transport would increase, as observed.

The initial stages in the action of an insecticidal delta-endotoxin of Bacillus thuringiensis var. israelensis on the epithelial cells of the malpighian tubules of the insect, Rhodnius prolixus

The effects of the 27 X 10(3) Mr insecticidal delta-endotoxin from Bacillus thuringiensis var. israelensis have been studied using, as a model system, isolated insect Malpighian tubules. At all concentrations of the toxin higher than 1 microgram ml-1 (4 X 10(−8) moll-1) applied to the outer surface of the tubules, fluid secretion failed within about 30 min. Except at very high concentrations, where failure always takes at least 30 s, there was an inverse relationship between the concentration of toxin and the time of failure of toxin-treated tubules. During exposure to toxin, the tubules were initially unaffected for a relatively long period and then rapid failure occurred. If the tubules were removed into toxin-free saline just before failure would have occurred, fluid secretion remained normal for at least 2 h, but on return to the origin toxin-containing saline failure was almost immediate. The toxin was found not to bind to the basement membrane. Ultrastructural changes became evident as tubule failure occurred. These initially involved modifications to the basal side of the cells, but later also to the luminal microvilli. Intercellular junctions became disassociated and cytoplasmic vacuolization occurred. The population of intramembranous particles in the basal membranes became reduced with time. Our findings suggest the following hypothesis for the initial stages in the interaction of the toxin with the tubules. Toxin molecules attach to the accessible cell membranes progressively and irreversibly. They do not readily associate by diffusing laterally in the membrane, so that toxic effects develop only when sufficiently large numbers of them attach close together. The molecules may then associate in some way as a complex, perhaps forming a pore in the membrane. Relatively few such pores lead rapidly to cell failure and death.

Maintenance of function in single epithelial cells spatially isolated from similar cells

We have found in an insect tissue, the Malpighian tubules of Rhodnius, instances of single epithelial cells which, as the result of a possible error in development, lie within the epithelium some distance from the main population of similar cells. This spatial separation makes it possible to measure the transport abilities of these cells. Their transport abilities were found to be the same as the cells in the main population. This finding shows that the maintenance of function in individual cells of epithelial tissues may not depend on direct contact with other similar cells.