Prof Tim Levine
Professor of Cell Biology
Institute of Ophthalmology
Faculty of Brain Sciences
- Joined UCL
- 16th Mar 2000
We mostly work on the broad biological question of how lipids and proteins interact inside cells, using budding yeast, a genetically tractable model system. Understanding lipid metabolism is of great medical importance for diseases prevalent in the Western world, including important ophthalmic diseases (such as Age-related macular degeneration), major brain disorders (Alzheimer's and Parkinson's), and also atherosclerosis and cardiovascular disease. Many important aspects of intracellular lipid metabolism are conserved between humans and yeast, so that new understanding gained in the single celled organism is highly relevant for eukaryotes in general.
This work focuses on lipid traffic across narrow cytoplasmic gaps where organelles come very close to each other. These membrane contact sites are very poorly understood because they are put together by multiple bridging complexes, and the routes of traffic are circular. Therefore, the traditional genetic approach of finding mutants that lack lipid traffic has often failed for membrane contact sites. Instead, we rely on a candidate approach, using bioinformatics tools to predict which proteins are likely to be involved.
Our first major discovery in this field was that VAP, a conserved endoplasmic reticulum protein, binds to a large variety of proteins by picking out a short stretch of primary sequence we named the FFAT motif that we found using PROSITE. This was initially found in proteins that transfer lipids between organelles, but has since been found to be the only way for cytoplasmic proteins to access the endoplasmic reticulum. Binding to VAP allows lipid transfer proteins to form bridges between the endoplasmic reticulum (where most lipids are made) and other organelles to which lipid is transferred.
From this we moved to discover and study a brand new family of lipid transfer proteins which are anchored at membrane contact sites. We identified this family with the structural bioinformatics tool HHsearch. This tool has been highly useful in the lab as a fast and accurate way to identify remote homology between proteins that share almost no identifiable sequence. The tool allows us to find which proteins share the same fold, so are likely to have evolved from a common ancestor.
Evolving from our specific use of this tool to make advances in lipid traffic at contact sites, we have made other bioinformatic discoveries, for example identifying the translated product of the C9ORF72 gene as DENN-like. We have bench-marked the likely extent of new prediction and discovery by HHsearch genome-wide. In yeast it may reduce unknown regions by one third (from current level of 15% of ORFs to 10%). To disseminate this knowledge, we have teamed up with the UCL Department of Computer Science to create a S. cerevisiae whole-genome HHsearch database, which will go live in 2017. It will be formatted to be compatible with the Saccharomyces Genome Database (SGD) for publication alongside the current Interpro dataset.
- University College London
- PhD, Immunology | 1993
- University College London
- MBBS, Pathology | 1986
- University of Cambridge
- BA, Pathology | 1983
University life outside research
I am active in the department's equality challenge team, joining in 2016 and becoming co-chair in 2017.
I am also honoured to be the co-chair of the UCL Athena Forum since it started in Jan 2018, bringing together all UCL departments' Athena and Equality/Diversity/Inclusion teams to speak with one voice and learn from each other.