My group’s aim is to understand the molecular mechanisms underlying the central control of food intake and body-weight. The approaches we have taken include:
1.) Understanding the physiological role of known genetic modifiers influencing food intake and body-weight. The first and most robust of the genes identified by GWAS is FTO (fat mass and obesity related transcript) and in the past 7 years, we have taken a number of different approaches to studying its biology. We have contributed to characterizing its enzymatic function as a demethylase (Gerken et al, Science 2007; Ma et al, Biochem J 2012), identifying and characterizing loss-of-function human mutations (Boissel et al, AJHG 2009; Meyre et al, Diabetes 2010) and determining its expression and direct role in the hypothalamus influencing food intake (Tung et al, PLoS ONE 2010). Whatever the explanation for the effects of intronic polymorphism on human adiposity, studies of humans and mice carrying genetic variants that functionally perturb FTO indicate that FTO itself is an important regulator of body size and composition. In the past two years, we have demonstrated a role for FTO in the cellular sensing of amino acids, linking levels to mTOR signalling (Cheung et al, IJO 2013; Gulati et al, PNAS 2013), and also determined that FTO shuttles between the nucleus and cytoplasm (Gulati et al, Biosci Rep 2014). Most recently, we have shown that FTO links high-fat feeding to leptin resistance through activation of hypothalamic NFкB-related signalling pathways (Tung et al, submitted). We also have a Wellcome Trust student currently working on the role of the non-coding RNAs Snord116 in the aetiology of Prader-Willi Syndrome.
2.) Identifying new players in the hypothalamic control of energy balance. We are interested in mapping the response of different hypothalamic nuclei to afferent nutritional signals, including circulating hormones such as leptin produced from fat and ghrelin produced from the gastrointestinal tract. We utilize either laser-capture microdissection to remove discrete regions of the hypothalamus (Tung et al, J Neurosci 2008; Jovanovic et al, J Neuroendo 2010), or FACS sorting of GFP labelled neurons and couple this to trancriptomic analyses using ‘next generation’ RNAseq.
3.) Developing novel bioinformatic tools, both for the analysis of next-generation sequencing data. We have, over the past few years, developed a novel solution to the processing of next-generation sequencing data, as the handling of such enormous amounts of data currently requires bioinformaticians and the use of expensive high-performance computing (HPC) clusters (Klus et al, BMC Res Notes 2012). We have developed BarraCUDA, a novel sequence alignment software that utilizes NVIDIA graphics cards to map sequencing reads to a reference genome, thus accelerating this process by 300% as compared to a standard workstation. BarraCUDA is designed with the aim of downsizing the NGS software pipeline from complex and expensive HPC clusters down to standard desktop computers.
I am deputy chairman of the British Society for Neuroendocrinology.