Pathogens, hosts, and their interactions – Intelligent search and visualisation of connected data
Infectious microbes are a major source of problems that threaten global food security, ornamental tree health, ecosystem resilience, and impose major costs on the UK farming and food industry. Additionally, there’s been an increase in resistance to antimicrobial compounds. With the ever increasing globalisation of trade and travel, infectious microbes also pose a significant monetary drain on UK medical and veterinary providers, threatening human and animal health and well being. A need for a resource that can tackle this while ensuring that it is Findable, Accessible, Interoperable, and Reusable (i.e. are FAIR) will benefit many different bioscience researchers.
The pathogen Host Interactions (PHI-base) database is a biological database which contains curated information on genes that are experimentally proven to affect the outcome of pathogen-host interactions. This is also supported alongside the newly developed tool called PHI-Canto, which focuses on recording the molecular interactions between the repertoires of small effect proteins produced by pathogens and their initial targets within each host species. It also focuses on the pathogen targets for anti-infective chemistries. This is supported alongside new generic PHIPO ontologies that are being developed to accurately describe the depth and breadth of pathogen-host interactions.
As useful as this data is, it is in a tabular format and is quite difficult to visualise. Likewise, there is no further annotation of the pathogen-host interactions, which could help us understand what other biological processes are at play and what other interactions occur for certain pathogen-host interactions. The KnetMiner team will bridge this gap by integrating PHI-data and ontologies alongside biological pathway, protein-protein interaction data, and other biological data from eight model organisms to elucidate the cascading processes triggered by pathogen effectors and their first targets in the host. This will enable multi-species and cross-kingdom network visualisation and analysis. The KnetMiner team plan to create biannual releases of the integrated knowledge base in FAIR compliant RDF and Neo4j graph formats. Already, there exists a Fusarium graminearum and Zymoseptoria tritici KnetMiner, with plenty more to come.
This project is in collaboration with Prof. Kim Hammond-Kosack, The KnetMiner team involved are Dr. Keywan Hassani-Pak, Joseph Hearnshaw, and Dr. Dan Smith.