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:
Understanding the physiological role of known genetic modifiers influencing food intake and body-weight
he 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.
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.
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.
Lam BYH, Cimino I, Polex-Wolf J, Kohnke SN, Rimmington D, Iyemere V, Heeley N, Cossetti C, Schulte R, Saraiva LR, Logan DW, Blouet C, O’Rahilly S, Coll AP & Yeo GSH. Heterogeneity of hypothalamic Pro-opiomelanocortin-expressing neurons revealed by single-cell RNA sequencing. (2017) Molecular Metabolism 6(5):383-392. PMID: 28462073
Raffan E, Dennis RJ, O’Donovan CJ, Becker JM, Scott RA, Smith SP, Withers DJ, Wood CJ, Conci E, Clements DN, Summers KM, German AJ, Mellersh CS, Arendt ML, Iyemere VP, Withers E, Söder J, Wernersson S, Andersson G, Lindblad-Toh K, Yeo GSH†, O’Rahilly S†. A deletion in the canine POMC gene is associated with weight and appetite in obesity prone Labrador retriever dogs. 2016 Cell Metabolism 10;23(5):893-900. († co-senior author). PMID: 27157046. PMCID: PMC4873617.
Tung YCL, Gulati P, Liu CH, Rimmington D, Dennis R, Ma M, Saudek V, O’Rahilly S, Coll AP, Yeo GSH. FTO is necessary for the induction of leptin resistance by high-fat feeding. Molecular Metabolism (2015) 4(4):287-98. PMID: 25830092. PMCID: PMC4354923.
Gulati P, Cheung MK, Antrobus R, Church C, Harding H, Tung TCL, Rimmington D, Ma M, Ron D, Lehner PJ, Ashcroft F, Cox RD, Coll AP, O’Rahilly S and Yeo GSH. (2013). A role for the obesity-related FTO gene in the cellular sensing of amino acids. Proc. Natl. Acad. Sci. U.S.A. www.pnas.org/cgi/doi/10.1073/pnas. 1222796110. PMID: 22614055.
Yeo GSH and Heisler LH. (2012). Unravelling the brain regulation of appetite: Lessons from genetics. Nat Neurosci, 15(10):1343-9. PMID: 23007189.
Cheung MK, Gulati P, O’Rahilly S, Yeo GSH. FTO expression is regulated by availability of essential amino acids. 2013 May;37(5). Int J Obesity (Lond). 744-7; doi: 10.1038/ijo.2012.77; Epub 2012 May 22. PMID: 22614055
Ma M, Harding HP, O’Rahilly S, Ron D and Yeo GSH. (2012). Kinetic analysis of FTO (Fat mass and obesity related) reveals that it is unlikely to function as a sensor for 2-oxoglutarate. Biochem J, 2012 Mar 21. PMID: 22435707.
Meyre D, Proulx K, Kawagoe-Takaki H, Vatin V, Gutiérrez-Aguilar R, Lyon D, Ma M, Choquet H, Horber F, Van Hul W, Van Gaal L, Balkau B, Visvikis-Siest S, Pattou F, Farooqi IS, Saudek V, O’Rahilly S, Froguel P, Sedgwick B, Yeo GSH. (2010). Prevalence of loss-of-function FTO mutations in lean and obese individuals. Diabetes, 59(1):311-8. PMID: 19833892. PMCID: PMC2797938.
Tung YCL, Ma M, Piper S, Coll AP, O´Rahilly S and Yeo GSH. (2008). Novel leptin-regulated genes revealed by transcriptional profiling of the hypothalamic paraventricular nucleus. J Neuroscience, 28(47):12419-26. PMID: 19020034. PMCID: PMC2650686.
Yeo GSH, Hung C.C, Rochford J, Keogh J.M, Gray J, Sivaramakrishnan S, O’Rahilly S and Farooqi I.S. (2004). A de novo mutation affecting human TrkB associated with severe obesity and developmental delay. Nature Neuroscience, 7(11):1187-9. PMID: 15494731.
Yeo GSH, Farooqi I.S, Aminian S, Halsall D.J, Stanhope R.G and O’Rahilly. (1998). A frameshift mutation in MC4R associated with dominantly inherited human obesity. Nature Genetics, 20(2):111-2. PMID: 9771698.