The Genetic Basis of Obesity and Neuronal Control of Energy Balance in Drosophila melanogaster
My lab’s focus is on uncovering the genetic and neuronal basis of obesity. Obesity is a complex disorder with a strong genetic component. Moreover, body weight is influenced by a variety of tissues and organs throughout the body, not just those where fat is stored. Indeed, many obesity-predisposing genes are expressed primarily in the brain, but we understand few of the pathways by which the central nervous system maintains energy homeostasis. Accordingly, at the forefront of obesity research are model systems allowing tissue-specific analysis of gene function in an organismal context. In the Reis lab we apply genetics, molecular biology and biochemistry techniques as well as behavioral analysis to identify and characterize neuronal and genetic factors controlling organismal fat storage using Drosophila melanogaster as a model system.
Neuronal regulation of metabolism
There are multiple mechanisms by which neurons in the brain could regulate body fat. Signaling molecules produced both outside and within the CNS trigger specific neuronal responses in the brain, allowing the brain to coordinate processes that occur in distinct tissues, including the storage and usage of body fat. For example, insulin (or insulin-like peptides, in Drosophila) produced by the brain and other tissues is used to monitor nutritional status in order to maintain energy balance through regulation of food intake and levels of circulating carbohydrates. However, despite significant progress in understanding the specific regions of the brain responsible for coordinating the production and detection of relevant signaling molecules, we have only an incomplete picture of the various mechanisms that neurons use to control body fat levels. We described genetic dissection of a group of neurons within the CNS of the Drosophila larva that regulate fat storage. The E347 group of neurons expand from the pars intercerebralis (PI), mushroom body (MB), subesophageal ganglion (SOG) and ventral nerve cord (VNC). In an unbiased approach, we identified Arc1, homolog of the Arc protein in mammals (also called Arg3.1) as a key factor in E347 control of body fat, allowing us to infer that the E347 neurons necessary for fat regulation are those that neighbor Arc1-expressing cells. Arc in mammals has been implicated in many molecular processes, including control of cytoskeletal remodeling at post-synaptic dendrites, endocytosis of AMPA receptors and transcriptional accumulation in response to diverse learning tasks. However, the precise mechanism by which Arc and its orthologs in other species regulate neuronal function remain unclear. Interestingly, relative to other immediate early genes rodent Arc is more highly induced during specific behaviors, particularly certain kinds of learning tasks. In brains of animals in which the synaptic activity of E347 neurons was experimentally activated, we found specific upregulation of Arc1 transcript relative to other immediate early genes, pointing to a specific role for Arc1 protein in body fat regulation downstream of E347 neurons. By pinpointing specific neuronal molecules acting in this and other circuits, our research represents a major step forward in understanding the neuronal mechanisms of body fat regulation.
Immunostaining of E347>GFP brains: green or red show anti-GFP or anti-Arc1 antibodies, respectively (Developmental Biology 2015, PMID: 26209258)
Genetic contributions of obesity
All animals need energy to fuel development and survive as adults. Excess energy stored as fat provides a means to endure periods when external energy is unavailable, but there is a delicate balance between accumulating sufficient fat stores and becoming obese. While the enzymes that mediate energy deposition into and mobilization from fat stores are well studied, the complex upstream regulatory pathways have not been fully worked out. We found that two members of a conserved family of RNA-binding proteins, Spen and Nito, operate in fat storage cells in fruit fly larvae to control the expression of genes that mediate energy liberation from fat stores. Manipulating Spen or Spenito function grossly perturbs larval energy metabolism, including imbalances in the amounts of stored fats, key metabolites, and metabolic enzymes, and resulting in defects in survival under starvation conditions. Interestingly, Nito opposes Spen functions, indicative of a regulatory mechanism that helps keep energy balance in check. We found that the mouse homologs of Spen and Nito, which were known to regulate gene expression in other pathways, respond similarly to changes in body fat induced by a high-fat diet, suggesting that the balancing effect of these two proteins also prevents mammalian obesity.
Model: Spen family members counter-regulate metabolism. Our model predicts that Spen and Nito bind the same or similar RNAs via the RRMs as well as transcription factors via the SPOC domain. Spen acts to activate enzymes key for the mobilization of energy stored as fat while Nito antagonizes this function. Spen may achieve this activation by binding additional factors in the uncharacterized region between the RRMs and SPOC domain not found in Nito. (PLoS Genetics, 2017, PMID: 28640815)
We continue to analyze the functions of other genes that we implicated in fat storage via unbiased genetic screens. We are using both the Drosophila model and also studying the mouse orthologs of fly genes that directly regulate fat storage in the fly fat storage organ, using cultured mouse adipocytes to identify those that also control mammalian fat storage in an autonomous manner. Based on our past successes, we expect to generate significant insights into the multigenic nature of obesity, and identify new targets for future treatments. (This project is the focus of a funded R01, DK106177).
Multiple animal models have been developed in order to try to better understand the onset and development of obesity and derived metabolic disorders, the complexity of which present profound challenges to research. Gene-diet interactions (i.e., how genetic background influences an individual's response to a given diet) are even more complex, illustrated by the difficulty in predicting outcomes of interventional diets. In general, the dietary components considered relevant to weight management are lipids, carbohydrate, and protein. Manipulating both the relative and absolute amounts of these components in the diets of model organisms leads to a variety of effects on body weight, body fat, overall metabolism, and longevity, among other biological parameters. However, simultaneously varying the genetic background to identify the underlying molecular pathways is only feasible in models amenable to unbiased genetic screens. We developed a synthetic Drosophila diet on which larvae develop at rates approaching those observed on rich diets. We determine the effects on development, size, total body fat levels, feeding behavior and lifespan of increasing levels of specific macronutrients (carbohydrates, lipids or protein). On a carbohydrate-rich diet, larvae had elevated triacylglycerides (TAGs), developed more slowly into smaller pupae, and, as adults, displayed changes in age-associated mortality. By contrast, on a protein-rich diet, larvae did not accumulate extra TAGs, and developed faster with no changes in size when compared to their sibling controls fed a normal diet. These findings emphasize the requirement of balanced diets for optimal development, growth and lifespan. Moreover, the diets described here offer an additional option for the analysis of macronutrient effects on various parameters of organismal metabolism in Drosophila. PLoS One, 2016, PMID: 26741692).
Numerous techniques exist to measure levels of stored fat in Drosophila, but most are expensive and/or laborious and have clear limitations. As a postdoc, I developed a novel assay for body fat in Drosophila larvae based on the differential density of fat versus lean tissues, allowing for extremely quick screening of a large number of animals while being both inexpensive and non-invasive. The site containing our protocol and video has since been viewed by researchers from >150 different institutions all over the world.
Wt or adp mutant larvae were immersed in the same concentration sucrose solution in plastic cuvettes and photographed after reaching equilibrium. Arrows, top of solution; arrowheads, bottom of solution. (Journal of Visualized Experiments, 2016,PMID: 27842367).
Hazegh KE, Nemkov T, D'Alessandro A, Diller JD, Monks J, McManaman JL, Jones KL, Hansen KC, Reis T. (2017) An autonomous metabolic role for Spen. PLoS Genetics;13(6):e1006859. doi: 10.1371/journal.pgen.1006859.
Hazegh KE, Reis T. (2016) A Buoyancy-based Method of Determining Fat Levels in Drosophila. Journal of Visualized Experiments 117. doi: 10.3791/54744.
Reis, T. (2016) Effects of Synthetic Diets Enriched in Specific Nutrients on Drosophila Development, Body Fat, and Lifespan. PLoS ONE 11(1): e0146758. doi: 10.1371/journal.pone.0146758.
Mosher, J., Zhang, W., Blumhagen, R.Z., D'Alessandro, A., Nemkov, T., Hansen, K.C., Hesselberth, J.R. and Reis, T. (2015) Coordination between Drosophila Arc1 and a specific population of brain neurons regulates organismal fat. Developmental Biology, 405(2):280-90. doi: 10.1016/j.ydbio.2015.07.021.
Reis, T.*, Van Gilst, M.R. and Hariharan, I. K.* (2010). A buoyancy-based screen of Drosophila larvae for fat-storage mutants reveals a role for Sir2 in coupling fat storage to nutrient availability. PLoS Genetics 6, e1001206. doi: 10.1371/journal.pgen.1001206
Reis, T. and Hariharan, I. K. (2005). Melting fat away in flies. Cell Metabolism 2, 82-84.