University of California, San Francisco
N412 C Genentech Hall
600 16th Street
San Francisco, CA 94143
2004 Searle Scholar
Analysis of genetic and neuronal networks that regulate fat content
Regulation of fat content involves a complex interplay between central regulators of feeding behavior in the nervous system, neuroendocrine signals, and metabolic regulators of energy expenditure and fat storage. We use genetic, cellular, and molecular approaches for understanding the networks that underlie the regulation of body fat in C. elegans. By combining classical mutagenesis screens with RNA-mediated interference to disrupt the expression of thousands of individual worm genes, we have identified over 500 genes that, when inactivated, affect body fat content in worms. These fat regulatory genes include receptors, channels, signal transduction molecules, transcription and translation factors, vesicular transporters, metabolic enzymes, and a number of genes with unassigned functions. The shared ancestry of the known mammalian and worm fat regulatory genes suggest that many of these newly identified genes may also function in human fat regulation.
Our goals are i) to understand the molecular functions and modes of regulation of the newly identified genes, ii) to understand the principles that govern how hundreds of genes whose products are expressed in multiple tissues network to regulate a complex physiological process, iii) to delineate the neuronal networks that regulate food intake and energy expenditure in worms, and iv) to extend these findings to identify mammalian fat and obesity genes and analyze how misregulation of these genes result in obesity associated diseases such as diabetes.
To decipher the modes of function of the newly identified genes, we are establishing genetic interaction networks between various mutants and RNAi clones that cause fat reduction or fat increase. We take advantage of suppressor/enhancer screens to disentangle the complex feedback loops that affect body fat.
Fat regulatory genes can be broadly classified as those that impact food intake or energy expenditure. Thus, we measure each of these parameters in the mutant animals or animals exposed to each fat regulatory RNAi clone.
Fusion of GFP tags to fat regulatory proteins allows for monitoring cellular expression and subcellular localization of each of the fat regulatory genes. These GFP fusions classify the genes directly involved in fat storage and utilization or those that function as neuronal regulators of feeding and energy expenditure. These experiments categorize the RNAi clones into subsets with related functions. For example, kinases within a group would be likely to phosphorylate the metabolic enzymes or transcription factors of the same group. Moreover, we can determine whether the expression or localization of a given fat regulatory gene is regulated by extrinsic or intrinsic signals such as fat levels, food, developmental stage, and other fat regulatory genes. Finally, since the complete map of the worm neuronal connections has been described, cellular localization of fat regulatory proteins could delineate the neuronal networks that regulate feeding behavior and energy expenditure. We can then test our hypothesis using a combination of laser ablation of specific neurons and single neuron gene expression studies.
Importantly, these types of analyses can be applied to many C. elegans genes whose mammalian homologs have been implicated in diseases of fat and sterol metabolism. In collaborative studies, findings from C. elegans are being extended to rodent models of obesity. Finally, genes discovered in C. elegans point to candidate obesity or diabetes loci within the large genomic regions identified in human pedigree and rodent studies. In other collaborative studies, candidate genes from collections of obese or diabetic pedigrees will be sequenced to identify variants.