Thomas Lawson

University of Birmingham


Exploring the Daphnia magna metabolome through novel computational methods of storage, analysis and multi-omic data integration


Primary: Mark Viant Co-supervisors: Warwick Dunn, John Colbourne and Peter Li (Gigascience)

PhD Summary

Daphnia have been under investigation in the field of ecology for over a century. However, they have also been used extensively as a model to investigate evolution, human health and as an indicator genus used to set ecotoxicological regulatory standards. The sequenced genome of Daphnia pulex provided valuable information for all the above fields but to understand the system wide mechanisms of pathways and reactions for Daphnia it is crucial to understand its metabolome. The central theme of this PhD project is to develop and apply computational methods to aid in the creation and investigation of the Daphnia magna metabolome. The PhD builds upon data being generated from the Deep Metabolome Annotation (DMA) project, an extensive characterisation of theDaphnia magna metabolome using novel mass spectrometry (MS) methods. The “un-targeted” approach attempts to identify as many known and unknown metabolites in Daphnia as possible. With this aim, computational methods for optimising liquid chromatography and MSn workflows are being developed to help create the Daphnia magna metabolome. A database for the data and meta data for the DMA project is also being created to allow for extensive data mining and spectral matching to explore the metabolome. The project will also involve integrating the metabolome with transcriptomic data and in silico genomic scale metabolic reconstructions. The project will work closely with the CASE partner Gigascience to make these computational tools and methods developed easily accessible to the scientific community through the Galaxy project.