A framework for community curation of interspecies interactions literature

  1. Alayne Cuzick
  2. James Seager
  3. Valerie Wood
  4. Martin Urban
  5. Kim Rutherford
  6. Kim E Hammond-Kosack

  • Curated by eLife

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    eLife assessment

    This valuable study reports improvements in methods and tools for curating complex pathogen-host interactions. A compelling framework is described, using rigorous approaches and to considerable extent validated by the biocuration community. The developed ontologies and controlled vocabularies could be extended beyond host pathogens, e.g. ecological contexts with multi-species and multilevel interactions.

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Abstract

The quantity and complexity of data being generated and published in biology has increased substantially, but few methods exist for capturing knowledge about phenotypes derived from molecular interactions between diverse groups of species, in such a way that is amenable to data-driven biology and research. To improve access to this knowledge, we have constructed a framework for the curation of the scientific literature studying interspecies interactions, using data curated for the Pathogen–Host Interactions database (PHI-base) as a case study. The framework provides a curation tool, phenotype ontology, and controlled vocabularies to curate pathogen–host interaction data, at the level of the host, pathogen, strain, gene, and genotype. The concept of a multispecies genotype, the ‘metagenotype,’ is introduced to facilitate capturing changes in the disease-causing abilities of pathogens, and host resistance or susceptibility, observed by gene alterations. We report on this framework and describe PHI-Canto, a community curation tool for use by publication authors.

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  1. Version published to 10.7554/elife.84658 on eLife
  2. eLife

    eLife assessment

    This valuable study reports improvements in methods and tools for curating complex pathogen-host interactions. A compelling framework is described, using rigorous approaches and to considerable extent validated by the biocuration community. The developed ontologies and controlled vocabularies could be extended beyond host pathogens, e.g. ecological contexts with multi-species and multilevel interactions.

  3. eLife

    Reviewer #1 (Public Review):

    This study presents a resource aiming to unify language and rules used in the literature to describe, curate and assess biology experiments, published or not. Focusing on host-pathogen interactions, the work presents a new ontology and controlled vocabulary, as well as rules to describe 'metagenotypes', a term coined for the joint description of interacting host-pathogen genotypes. 'PHI-Canto' extends a previous resource by also enabling using UniProtKB IDs to curate proteins. Among other important by-products, PHI-Canto could contribute to damping proliferating names and acronyms for genes, processes, and interactions; a chronic annoyance in the biosciences.

    The tool does give the impression that, with sufficient time and usage, it could become a rich and robust resource. Just addressing the Uniprot IDs issue is a nice move.

  4. eLife

    Reviewer #2 (Public Review):

    In this paper, the authors propose a system for annotating and curating scientific publications in the context of interspecies host-pathogen interactions. This system, called PHI-Canto (the Pathogen-Host Interaction Community Annotation Tool), is an extension of an existing tool (called Canto). In addition, they present the development of new concepts, controlled vocabularies, and an ontology for annotating relevant aspects in this domain, called PHIPO (Pathogen-Host Interaction Phenotype Ontology).

    The approach has been empirically validated by annotating ten publications. The application's source code is available, as well as the associated ontologies and vocabularies and an example of the data resulting from the annotation process.

  5. eLife

    Reviewer #3 (Public Review):

    In this work, the authors have built a framework for the annotation of interactions between species. The framework includes ontologies, methodologies, and an annotation tool called PHI-Canto. The framework makes use of multiple existing ontologies that are in wide use in the biocuration community. In addition, the authors have built their own project-specific controlled vocabularies and ontologies for the capture of pathogen-host interaction phenotypes (PHIPO), diseases (PHIDO), and environmental conditions (PHI-ECO). Their work builds on and extends methods that have been developed within the Gene Ontology Consortium and model organism databases. The tool PHI-Canto is an extension of the tool Canto developed by PomBase for curation. The authors used this framework to annotate pathogen-host interactions within the Pathogen-Host Interactions Database.

    Strengths: The manuscript is well-written and includes significant detail regarding curation policies/methods and the use of the actual PHI-Canto tool. The appendices are very detailed and provide useful illustrations of the annotation practices and tool interface. The work has built upon and extended well-established standards and methods that have proven their utility over many years of use in the biocuration community. The authors have rigorously tested their framework with the curation of a variety of publications providing a diverse assortment of annotation challenges. The concept of a "metagenotype" is important and providing such a structured system for the capture of this information is useful. All of the materials produced by the work are completely freely available for use by the wider community.

    Weaknesses: There are some areas of the manuscript and appendices which are a bit confusing and could be improved. The authors have developed their own set of disease terms (PHIDO) but do not comment on why existing disease terminologies (such as Mondo or DO) were not used or if the PHIDO terms relate to those other vocabularies. There is no discussion of the possible use of a graph representation for the capture of this complex information (which is being done in many settings including the Gene Ontology with GO Causal Activity Models (GO-CAMs)) or why such a structure was not used. Although the abstract talks about the use of the framework within the PHI database as a test case for broader use regarding interspecies interactions, there is no mention of extending the use of the tool to other species interaction communities beyond pathogen-host interactions.

  6. eLife

    Author Response:

    Reviewer #1 (Public Review):

    This study presents a resource aiming to unify language and rules used in the literature to describe, curate and assess biology experiments, published or not. Focusing on host-pathogen interactions, the work presents a new ontology and controlled vocabulary, as well as rules to describe 'metagenotypes', a term coined for the joint description of interacting host-pathogen genotypes. 'PHI-Canto' extends a previous resource by also enabling using UniProtKB IDs to curate proteins. Among other important by-products, PHI-Canto could contribute to damping proliferating names and acronyms for genes, processes, and interactions; a chronic annoyance in the biosciences.

    The tool does give the impression that, with sufficient time and usage, it could become a rich and robust resource. Just addressing the Uniprot IDs issue is a nice move.

    We thank the reviewer for their positive comments and acknowledgement of the importance of using unified language in literature curation. We are pleased to see that our effort to improve interoperability and use existing resources has been recognized. We are also pleased that this reviewer recognizes the additional benefits of choosing to use UniProtKB accession numbers.

    Reviewer #2 (Public Review):

    In this paper, the authors propose a system for annotating and curating scientific publications in the context of interspecies host-pathogen interactions. This system, called PHI-Canto (the Pathogen-Host Interaction Community Annotation Tool), is an extension of an existing tool (called Canto). In addition, they present the development of new concepts, controlled vocabularies, and an ontology for annotating relevant aspects in this domain, called PHIPO (Pathogen-Host Interaction Phenotype Ontology).

    The approach has been empirically validated by annotating ten publications. The application's source code is available, as well as the associated ontologies and vocabularies and an example of the data resulting from the annotation process.

    We thank the reviewer for their positive comments on our framework for curating interspecies interactions literature. We are pleased that the reviewer has recognized that the source code, associated ontologies and curated data are freely available for others to use. We are delighted that the reviewer found the curation of ten trial publications in PHI-Canto informative and benefited from the worked curation examples.

    Reviewer #3 (Public Review):

    In this work, the authors have built a framework for the annotation of interactions between species. The framework includes ontologies, methodologies, and an annotation tool called PHI-Canto. The framework makes use of multiple existing ontologies that are in wide use in the biocuration community. In addition, the authors have built their own project-specific controlled vocabularies and ontologies for the capture of pathogen-host interaction phenotypes (PHIPO), diseases (PHIDO), and environmental conditions (PHI-ECO). Their work builds on and extends methods that have been developed within the Gene Ontology Consortium and model organism databases. The tool PHI-Canto is an extension of the tool Canto developed by PomBase for curation. The authors used this framework to annotate pathogen-host interactions within the Pathogen-Host Interactions Database.

    Strengths: The manuscript is well-written and includes significant detail regarding curation policies/methods and the use of the actual PHI-Canto tool. The appendices are very detailed and provide useful illustrations of the annotation practices and tool interface. The work has built upon and extended well-established standards and methods that have proven their utility over many years of use in the biocuration community. The authors have rigorously tested their framework with the curation of a variety of publications providing a diverse assortment of annotation challenges. The concept of a "metagenotype" is important and providing such a structured system for the capture of this information is useful. All of the materials produced by the work are completely freely available for use by the wider community.

    Weaknesses: There are some areas of the manuscript and appendices which are a bit confusing and could be improved. The authors have developed their own set of disease terms (PHIDO) but do not comment on why existing disease terminologies (such as Mondo or DO) were not used or if the PHIDO terms relate to those other vocabularies. There is no discussion of the possible use of a graph representation for the capture of this complex information (which is being done in many settings including the Gene Ontology with GO Causal Activity Models (GO-CAMs)) or why such a structure was not used. Although the abstract talks about the use of the framework within the PHI database as a test case for broader use regarding interspecies interactions, there is no mention of extending the use of the tool to other species interaction communities beyond pathogen-host interactions.

    We thank the reviewer for their detailed response. We are pleased that the reviewer found the manuscript to be well-written and informative with useful examples. We thank the reviewer for their helpful suggestions to improve the appendices and manuscript text.

    We would like to clarify that PHIDO is not intended to compete with existing disease ontologies: it is instead being used as a placeholder, until the time when its terms can be replaced with terms from existing disease ontologies. PHIDO was an expedient solution, in the sense that it provided the fastest way for us to test the process of curating diseases with PHI-Canto. This is because we only had to convert the existing list of disease names already in PHI-base into a controlled vocabulary, thus removing the need to wait for maintainers of other ontologies to add terms for us (as reported in Urban et al., 2022).

    Additionally, we were required to use terms from PHIDO due to the lack of representation for plant and animal diseases in existing ontologies or vocabularies. Plant disease, in particular, is very underrepresented, with the ontologies we surveyed having either inappropriate semantics (e.g. the Plant Trait Ontology focusing on traits related to disease, rather than the diseases themselves) or still being in development (e.g. the Plant Stress Ontology). The majority of source ontologies used by MONDO are human-centric, and DO is exclusively for human disease, yet human disease represents only part of the focus of PHI-base (~35%). Furthermore, our choice of vocabularies is limited by the fact that Canto currently only supports ontologies in OBO format (for historical reasons).

    We have begun the process of harmonizing disease names in PHI-base with terms from existing disease ontologies – such as MONDO, DO, and the National Cancer Institute Thesaurus – with the ultimate aim of using terms from those ontologies in curation, instead of terms from PHIDO. As general vocabularies for animal and plant disease emerge or are identified, we will extend this procedure to those diseases.

    With regards to a graph representation of the data, we are aware of the examples the reviewer described, and we agree that this type of representation could be preferable. However, our data model is currently constrained by the developers of Canto, who use a relational data model and currently have no plans to implement a graph data model or a graph representation. We acknowledge that query languages like GraphQL can provide a graph-based interface to an existing relational data model, but we believe this would require a significant technological investment. For PHI-base, we plan to enable a graph representation of the data by integrating with existing knowledge graph tools, such as KnetMiner (www.knetminer.com;doi.org/10.1111/pbi.13583), which will provide graph-based queries on PHI-base (albeit only on select species for which knowledge graphs will be provided, i.e. Arabidopsis, rice, wheat, eight plant and human infecting fungal ascomycete pathogens, and two non-pathogenic yeast species). We will also use KnetMiner integration to embed subgraphs of the complete knowledge graph into the gene-centric pages on the PHI-base 5 website.

    We acknowledge the lack of discussion about extending the tool for broader interspecies interactions. These examples may have been omitted from a previous draft due to journal word count limits. Possible future uses of the PHI-Canto schema could include insect–plant interactions (both beneficial and detrimental), endosymbiotic relationships such as mycorrhiza–plant rhizosphere interactions, nodulating bacteria–plant rhizosphere interactions, fungi–fungi interactions, plant–plant interactions or bacteria–insect interactions, and non-pathogenic relationships in natural environments, such as bulk soil, rhizosphere, phyllosphere, air, freshwater, estuarine water or seawater, and tissues or organs (e.g. the gut, lungs, and skin of humans, birds, or other animals). The schema could also be extended to situations where phenotype relations to genes or genotypes have been established for predator–prey relationships, or where there is competition in herbivore–herbivore, predator–predator, or prey–prey relationships in the air, on land or in the water. Customizing Canto to use other ontologies and controlled vocabularies is as simple as editing a configuration file within the source code.

  7. Version published to 10.1101/2022.12.15.520601v1 on bioRxiv