Royal (Dick) School of Veterinary Studies / The Roslin Institute
Microbes dominate life on Earth - there are an estimated 10 trillion microbial species (10.1073/pnas.1521291113), Bacteria alone represent two thirds of the known biodiversity on our planet (10.1038/nmicrobiol.2016.48), and, despite their small size, microbes represent 16% of the Earth’s biomass (bacteria, archaea, fungi and protists represent 93 gigatons out of a total estimated biomass of 555 gigatons 10.1073/pnas.1711842115)).
The microbiome is the community of microbes that exist in any given environment, and the activity of these communities has been implicated in human, plant and animal health and disease, climate change, the health of our oceans, our soils and our built environments.
Current bioinformatics methods for analysing the microbiome focus almost entirely on Bacteria and Archaea, and ignore Protozoa and Fungi. The aim of this project is to develop methods for the assembly and analysis of Protozoa and Fungi from large metagenomic datasets.
Protozoa as an example of missing diversity: Not only do protozoa represent the dark matter of the microbiome, they are almost completely absent from genomic databases - only 94 protozoan genomes are present in RefSeq and only three of these are marked as complete. Part of the reason for this is that protozoa are incredibly hard to culture and study. Many protozoa have complex life cycles, stages of which may require very different culturing media and conditions. Success or failure to culture protozoa is influenced by a huge number of parameters such as life cycle stage, temperature, pH, availability of nutrients, media components, and the sterility of equipment. Visvesvara and Garcia (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC118078/
) state that even the choice of glass used for the culture container can have a major impact, and Newbold et al (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4659874/
) describe rumen protozoa as “impossible to maintain… in axenic culture”.
The Watson lab have been developing methods to assembly eukaryotic genomes from metagenomic datasets, based on identification of eukaryotic contigs followed by a seed-cluster approach. In this project, the student will develop these methods further, apply them to a range of public metagenomic datasets, and compare to 18S/ITS sequencing of archived samples.
The project will involve some wet-lab work, though will be primarily computational in nature.
The project will involve the use of advanced bioinformatics methods, such as engineering reproducible workflows, developing software environments and containers, and execution of large-scale analyses on the cloud. Training in all aspects will be available.
Expected outputs will be open source software; chapters (or papers) describing the methods and software; and chapters (or papers) describing the novel genomes discovered in a range of environments.
All candidates should have or expect to have a minimum of an appropriate upper 2nd class degree. To qualify for full funding students must be UK or EU citizens who have been resident in the UK for 3 years prior to commencement.