PhD in Marine Biology

Lipids, containing carbon, nitrogen, phosphorus and sulfur, are a major component of all living cells and are constantly released into the oceans due to programmed cell death, viral infections and zooplankton grazing. Current estimates suggest that lipids can account for ~10% of total dissolved organic matter (DOC) in the oceans. However, our knowledge on microbial lipid transformation in the oceans is very limited. Neither the identities of the microbes involved, nor the mechanisms by which lipids are degraded, have been well understood. A major hurdle in understanding the microbial lipid cycle lies in the difficulty in characterizing and quantifying numerous lipid classes in marine samples. Commonly observed lipids in marine ecosystems include phospholipids, glycolipids and amino acid-containing lipids. Recent advances in technologies such as liquid chromatography electrospray ionization mass spectrometry (LC-ESI-MS) has enabled high throughput identification and quantification of thousands of cellular lipid molecular species (Shevchenko, 2010), which now enables lipid characterization both qualitatively and quantitatively. Indeed, lipidomics is starting to complement the rapid progress made in genomics, metagenomics, transcriptomics and proteomics. Here in this project, we will combine laboratory and filed based methodologies to fully uncover the lipid cycle in marine waters. The aim of this project is thus twofold, Firstly, we aim to establish a high throughput workflow for simultaneous determination of common lipids species in marine surface waters using our in house HPLC MS platform. This will involve examining samples from the Western English Channel, collected via the Marine Biological Association research vessel, Sepia. Secondly, we aim to determine the identity and activity of key microbial populations in the recycling of representative lipids in marine surface waters and coastal marine sediment using integrated omics approach, e.g. high throughput sequencing of 16S/18S rRNA, metagenomics, metagenomics and lipidomics.