Metabolomic and Gene Expression Profiles Exhibit Modular Genetic and Dietary Structure Linking Metabolic Syndrome Phenotypes in Drosophila

Abstract

Genetic and environmental factors influence complex disease in humans, such as metabolic syndrome, and Drosophila melanogaster serves as an excellent model in which to test these factors experimentally. Here we explore the modularity of endophenotypes with an in-depth reanalysis of a previous study by Reed et al. (2014), where we raised 20 wild-type genetic lines of Drosophila larvae on four diets and measured gross phenotypes of body weight, total sugar, and total triglycerides, as well as the endophenotypes of metabolomic and whole-genome expression profiles. We then perform new gene expression experiments to test for conservation of phenotype-expression correlations across different diets and populations. We find that transcript levels correlated with gross phenotypes were enriched for puparial adhesion, metamorphosis, and central energy metabolism functions. The specific metabolites L-DOPA and N-arachidonoyl dopamine make physiological links between the gross phenotypes across diets, whereas leucine and isoleucine thus exhibit genotype-by-diet interactions. Between diets, we find low conservation of the endophenotypes that correlate with the gross phenotypes. Through the follow-up expression study, we found that transcript-trait correlations are well conserved across populations raised on a familiar diet, but on a novel diet, the transcript-trait correlations are no longer conserved. Thus, physiological canalization of metabolic phenotypes breaks down in a novel environment exposing cryptic variation. We cannot predict the physiological basis of disease in a perturbing environment from profiles observed in the ancestral environment. This study demonstrates that variation for disease traits within a population is acquired through a multitude of physiological mechanisms, some of which transcend genetic and environmental influences, and others that are specific to an individual’s genetic and environmental context.

Systems genetics of the Drosophila metabolome

“…Previous studies have associated genetic variation with metabolic phenotypes in human populations (Gieger et al 2008;Illig et al 2010;Suhre et al 2011;Shin et al 2014) and model organisms (Klenø et al 2004;Gilliland et al 2006;Keurentjes et al 2006;Martin et al 2007;Wentzell et al 2007;Schauer et al 2008;Fu et al 2009;Riedelsheimer et al 2012;Breunig et al 2014;Reed et al 2014;Williams et al 2015;Dumas et al 2016;Fernie and Tohge 2017;Swain-Lenz et al 2017). Disease-centered high dimensional multi-omic analyses have provided insight into the relationship between genetic variation and susceptibility to diseases (Hood et al 2004;Prabakaran et al 2004;Ibrahim and Gold 2005;Samuel et al 2008).…”

Drosophila as a Model for Diabetes and Diseases of Insulin Resistance

“…Finally, several studies from these researchers suggested that when populations were exposed to new environments, latent, or cryptic genetic variation was revealed that cannot be observed in long-term stable environments (Gibson & Reed, 2008; Reed et al, 2014, 2010). This may be particularly significant for diseases like MetS, insulin resistance, and T2D, for which dietary changes appear to have had large impacts on disease rates in human populations over a relatively short-time scale (Reed et al, 2014; Williams et al, 2015). Overall, these studies provide a wealth of information on the complexities of metabolic variation in flies that remains to be mined in the future and which will likely have high relevance for human populations.…”

Considerations when choosing a genetic model organism for metabolomics studies

“…We know the metabolome can vary greatly among genotypes within a species as well as across environments [2–5], and using genetically characterized models can assist in identifying the differences in the metabolome due to genetic and environmental effects (Figure 2). Many model organisms can be genetically engineered to test specific mechanistic questions, and panels of lines bearing mutations distributed across the model's genome are easily obtained ( e.g.…”

“…Some studies in flies have included a few tens of wild isolates, targeted toward capturing the variation among genotypes in the response to environmental factors. For example, Reed and colleagues quantified substantial genetic and dietary effects across 187 metabolites in a panel of 20 isofemale lines, and associated that variation with transcriptomic and disease phenotype variation [2,3]. Similar small-scale studies were conducted by Promislow and coworkers [38].…”

“…disease) works through a cascade of physiological levels, each of which affects the ultimate phenotype (Figure 1). Like all physiological levels, the metabolome is highly influenced by genetic, environmental, and genotype-by-environment interactions [2–5]; however, the proximity of the metabolome to the ultimate phenotype makes it an especially good measure of an organism's physiology [1]. Metabolomics is still in its early stages and has many unsolved challenges, such as chemically identifying metabolites [6].…”