What do we do?

1. The development of 'Gene Trapping' as a method to search for genes involved in any process that can be studied and meaasured in laboratory cells. A useful way to think about gene trapping is that it is like studying an entire human population in a dish. We are all genetically unique humans, with distinct combinations of genetic variation that have been shuffled and passed down from our ancestors. That's why individuals have very different genetic susceptibilities to disorders such as cancer, Alzheimers and diabetes - or sometimes different responses to therapeutic medication. It's important to uncover the genes and their variants that are behind these differences as this will lead to better drugs tailored to the individual patient. Classically, Human Genetics is the route to identify such connections. However, this requires collecting DNA samples from many individuals, and then using expensive and time-consuming methodologies to look for variants that are associated with the illness or biological phenomenon under study. Even after such effort, the links are complex and often of small effect. Sometimes, the complexity of the genetic differences between individuals can prove a barrier to gene identification: rare gene mutations in a person diagnosed with an illness can be likened to a room full of murderers - you know one of them 'did it', but it's hard to prove which one. Here's where Gene Trapping offers an alternative (and much cheaper) route. A human laboratory cell line is mutated by introducing a special stretch of DNA. If this drops into the middle of a gene, by chance, then that gene will be switched off in that cell. Because we use many thousands of cells in this process, by the end we have created a 'library' of cells - each with its own gene mutation. This library can be thought of as similar to the genetically diverse human population. Now we can ask any biological question of that library. For example: 'which mutant cells in the library fail to respond to this particular drug?', 'which mutant cells can't complete this biological process?', or 'which cells are resistant to infection by this microbe?'. At the end of the screen, we have isolated a set of cells containing mutations in genes that must be functionally important in that process - and simple molecular techniques can be used to reveal the gene identities. Note that I put the word 'functionally' in bold - why? Many genetic techniques such as microarrays and some human genetic approaches are based on 'association' and cannot separate cause and effect. An analogy to illustrate the problems with association might be that the common cold is associated with winter. Or watching a film at the cinema is associated with popcorn stuck between your teeth. At one level these observations are sort of true, but not really mechanistically informative - and prone to misinterpretation. You might try to wear a woolly hat to prevent contaging a cold. Imagine if you don't understand what a cinema is (we frequently don't understand biological systems). You might conclude that the cinema is where you go to cure popcorn in your teeth - a cause and effect confusion. Gene traps, by contrast, are functional because you look for a real response to an action (the mutation). They are like hitting yourself over the head with a hammer. It hurts, and there's no ambiguity about the cause. I'm painting a very rosy picture of gene traps. They are not perfect. Here are some issues: they only model one kind of mutation (gene loss-of-function) whereas, in real life, there are several; they are used in laboratory cell lines that can sometimes act very differently to cells growing in a living body; gene traps can sometimes cause 'dirty' or 'non-canonical' mutations where it becomes harder to pin down their effects to a specific gene; and lastly, not all genes can be mutated in this way. Nevertheless, I believe they can make a useful contribution to many biological questions (especially so, if married to Human Genetics data). Click here to view a much more detailed description of precisely what we are doing with gene trapping.
2. A collaboration with Dr David Watson on the identification of metabolomic biomarkers associated wtih mental illness. Metabolomics is one of the more recently defined 'omics' disciplines. It relates to the identification of the complete profile of small chemical entities (not DNA, RNA or proteins - they have their own 'omics') that exist in our cells, organs and circulatory system. Examples of these molecules include the lipids (fats), amino acids, carbohydrates (sugars), hormones, and co-factors. One of our goals is to identify metabolite 'biomarkers' that might be clinically useful to help diagnose mental illnesses such as schizophrenia, bipolar disorder, and depression. In the past, we identified which metabolites changed in the brain of mice that modelled a form of schizophrenia observed in patients who had a mutation in the NPAS3 gene. This told us that energy production from glucose was affected - and we also observed a significant increase in markers of inflammation (unpublished). We have now completed a new study into the relationship between the brain metabolite changes seen in schizophrenia, depression, bipolar disorder and diabetes - in comparison to healthy brains. The scientific literature has already revealed that there may be common genetic threads between the different psychiatric disorders, and our NPAS3 study highlighted the metabolic deficits in schizophrenia. The results of this latest study have just been submitted for publication but back up this idea of shared biological underpinnings and response to these devastating conditions.
3. A collaboration with Dr Hilary Carswell, Dr Katharine 'Chris' Carter and a local SME, Pharmacells, on the characterisation of a totally new mammalian cell type with some interesting properties. This work will be published in the future.
4. The study of epigenetic DNA changes associated with ageing. Shakhawan Mawlood is a PhD student working with me and Lynn Dennany in Forensic Science. Shakhawan is working on DNA methylation levels on normal chromosomes (autosomes) as well as that occuring in mitochondrial DNA. The object is to determine which sites have methylation levels that change with age.