Five year funding for international open-access databases for bacterial diversity

The Wellcome Trust has awarded the University of Oxford funding of £1.2 million over the next five years for PubMLST, an international web-based resource that has been operational in Oxford since 1998. 

PubMLST is an open-source repository of information on the diversity of microbes and is widely used for investigating disease epidemics, antimicrobial resistance, and the basic biology of microbes, with an especial emphasis on those causing human disease.

Professor Martin Maiden and Dr Keith Jolley in the Department of Zoology and Professor Angela Brueggemann at the Nuffield Department of Population Health lead the project, which will ensure the maintenance and development of the PubMLST microbial molecular typing website and its associated databases. This will further the dissemination and exploitation of bacterial genome diversity data for public health benefit, with an especial emphasis on accessibility and enhancing data re-use.

PubMLST provides a major international resource for the storage, analysis, and dissemination of assembled microbial whole genome sequence data and hosts over 100 databases that provide sequence typing nomenclature and link curated genetic, provenance, phenotype, and population data. The PubMLST resource uses the open-source software platform BIGSdb, specifically developed for this purpose, and ongoing development will facilitate complex data querying and comparative analyses through a web interface with data also retrievable automatically via a programming interface.

Over the next five years, the platform will be developed to make curation easier and improve third party data access. Visual analytic front-end tools, including interactive dashboards and storyboards, will be introduced to facilitate outreach to a wide audience, providing effective and intuitive means to investigate correlation, trends and patterns in submitted data, enabling users of all types and knowledge levels to interact with and explore the data.