A framework for community curation of interspecies interactions literature.
A framework for community curation of interspecies interactions literature.
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DOI：
10.7554/elife.84658
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发表时间：
2023-07-04
期刊：
影响因子：
7.7
通讯作者：
Hammond-Kosack KE
中科院分区：
文献类型：
--
作者：
Cuzick A;Seager J;Wood V;Urban M;Rutherford K;Hammond-Kosack KE
在生物学中生成和发布的数据的数量和复杂性大幅增加，但很少有方法可以捕获有关来自不同物种群体之间分子相互作用的表型的知识，以这种方式适合数据驱动的生物学和研究。为了更好地获取这些知识，我们构建了一个框架，用于管理研究物种间相互作用的科学文献，使用病原体-宿主相互作用数据库（PHI-base）的数据作为案例研究。该框架提供了一个策展工具，表型本体，和控制词汇，以策展病原体-宿主相互作用的数据，在主机，病原体，菌株，基因和基因型的水平。引入多物种基因型的概念，即“元基因型”，以便于捕捉病原体致病能力的变化，以及通过基因改变观察到的宿主抗性或易感性。我们报告这个框架，并描述PHI-Canto，一个社区策展工具，供出版物作者使用。研究社区产生的数据量越来越大，可能难以管理，这使得人类和计算机组织和连接来自不同来源的信息变得具有挑战性。目前，允许作者策划同行评议的生命科学出版物的软件工具仅针对单一物种或不相互作用的密切相关物种而设计。尽管大多数研究团体都在努力使他们的数据公平（可查找，可解释，可互操作和可重用），但基于两个或多个物种（物种间）之间的相互作用（如病原体-宿主相互作用）来管理详细信息特别困难。因此，缺乏支持多物种相互作用数据库的工具，导致对劳动密集型管理方法的依赖。为了解决这个问题，Cuzick等人使用病原体-宿主相互作用数据库（PHI-base）作为案例研究，该数据库从200多种期刊上发表的文本，表格和图表中收集知识。开发了一个框架，该框架可以捕获相互作用的许多可观察的性状（表型注释），并将它们直接与跨多个尺度（从微观到宏观）的这些相互作用中涉及的基因型组合联系起来。这表明，有可能建立一个软件工具框架，以便比以前更详细地管理物种之间的相互作用。Cuzick等人开发了一个名为PHI-Canto的在线工具，允许任何研究人员管理几乎任何已知物种之间已发表的病原体-宿主相互作用。一个本体-概念和它们的关系的集合-被创建来描述病原体-宿主相互作用的结果以标准化的方式。此外，一个新的概念，称为“元基因型”的发展，它代表了病原体和宿主基因型的组合，可以很容易地注释从每个相互作用产生的表型。新策划的关于病原体-宿主相互作用的多物种FAIR数据将使不同学科的研究人员能够比较和对比不同物种和规模的相互作用。最终，这将有助于制定新的方法，减少病原体对人类、牲畜、作物和生态系统的影响，目的是减少疾病，同时提高粮食安全和生物多样性。该框架是潜在的采用任何研究社区调查物种之间的相互作用，并可以适应探索其他有害和有益的物种间的相互作用。
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. The increasingly vast amount of data being produced in research communities can be difficult to manage, making it challenging for both humans and computers to organise and connect information from different sources. Currently, software tools that allow authors to curate peer-reviewed life science publications are designed solely for single species, or closely related species that do not interact. Although most research communities are striving to make their data FAIR (Findable, Accessible, Interoperable and Reusable), it is particularly difficult to curate detailed information based on interactions between two or more species (interspecies), such as pathogen-host interactions. As a result, there was a lack of tools to support multi-species interaction databases, leading to a reliance on labour-intensive curation methods. To address this problem, Cuzick et al. used the Pathogen-Host Interactions database (PHI-base), which curates knowledge from the text, tables and figures published in over 200 journals, as a case study. A framework was developed that could capture the many observable traits (phenotype annotations) for interactions and link them directly to the combination of genotypes involved in those interactions across multiple scales – ranging from microscopic to macroscopic. This demonstrated that it was possible to build a framework of software tools to enable curation of interactions between species in more detail than had been done before. Cuzick et al. developed an online tool called PHI-Canto that allows any researcher to curate published pathogen-host interactions between almost any known species. An ontology – a collection of concepts and their relations – was created to describe the outcomes of pathogen-host interactions in a standardised way. Additionally, a new concept called the ‘metagenotype’ was developed which represents the combination of a pathogen and a host genotype and can be easily annotated with the phenotypes arising from each interaction. The newly curated multi-species FAIR data on pathogen-host interactions will enable researchers in different disciplines to compare and contrast interactions across species and scales. Ultimately, this will assist the development of new approaches to reduce the impact of pathogens on humans, livestock, crops and ecosystems with the aim of decreasing disease while increasing food security and biodiversity. The framework is potentially adoptable by any research community investigating interactions between species and could be adapted to explore other harmful and beneficial interspecies interactions.