PhD: Whole genome metagenomics to determine land use effects on soil ecosystem services
CEH Wallingford
Email Briony Jones at Centre for Ecology and Hydrology
I completed a BSc in Biomedical Sciences at Brunel University before going on to undertake a Master’s degree in Computational Biology and Bioinformatics from the University of York. I have since been working at CEH Wallingford for a year as a Bioinformatician. Whilst undertaking my masters I conducted a four-month placement at Imperial College where I worked on a cross platform microarray meta-analysis pipeline, which aimed to combine experimental data in order overcome the issues of under sampling associated with individual studies. This experience alongside my interest in my MSc’s systems biology module lead me to develop an interest in big data analysis and to pursue a PhD relating to bioinformatics and functional networks.
Research Project:
My project will be based at CEH Wallingford and Bangor University’s School of Environment, Natural Resources and Geography. It will employ computational based approaches to analyse 100 soil metagenomes from different land use gradients across the UK to determine whether land use changes affect the soils ability to deliver ecosystem services (e.g. nutrient recycling, carbon storage, pesticide degradation and water purification).
The activities of microorganisms within the soil are known to contribute to ecosystem services, however there is a lack of knowledge as to how microbial biodiversity contributes to the provision of services. Understanding this subject is becoming increasingly important as it could influence policy maker’s decisions in order to ensure sustainable food production for growing populations.
Through analysing whole metagenome data, I hope to assess whether land management can be used as a reliable predictor for the occurrence of functional genes associated with ecosystem services. This analysis also has the potential to uncover unknown functional pathways in the soil and the existence of novel proteins that could be exploited for biotechnology (e.g. antibiotics).