The metabolome as a link in the genotype-phenotype map for peroxide resistance in the fruit fly, Drosophila melanogaster

Abstract

Background Genetic association studies that seek to explain the inheritance of complex traits typically fail to explain more than a small fraction of the heritability of the trait under study. Thus we are left with a gap in the map from genotype to phenotype. Several approaches have been used to fill this gap, including those that attempt to map endophenotype such as the transcriptome, proteome or metabolome, that underlie complex traits. Here we used metabolomics to explore the nature of genetic variation for hydrogen peroxide (H­2O2) resistance in the sequenced inbred Drosophila Genetic Reference Panel (DGRP). Results We first studied genetic variation for H2O2 resistance in 180 DGRP lines and identify the insulin signaling modulator u-shaped and several regulators of feeding behavior. We then profiled a portion of the aqueous metabolome in subsets of eight ‘high resistance’ lines and eight ‘low resistance’ lines. We used these lines to represent collections of genotypes that were either resistant or sensitive to the stressor, effectively modeling a discrete trait. Across the range of genotypes in both populations, flies exhibited surprising consistency in their metabolomic signature of resistance. Metabolomic profiles were also able to distinguish stress-resistant from stress-sensitive flies with greater accuracy than the genotype of these same lines. Furthermore, we found a metabolic response to H2O2 that was shared among sensitive, but not resistant genotypes. Metabolomic data further implicated at least two pathways, glycogen and folate metabolism, as determinants of sensitivity to H2O2. We also discovered a confounding effect of feeding behavior on assays involving supplemented food. Conclusions This work suggests that the metabolome can be a point of convergence for genetic variation influencing complex traits, and efficiently elucidate the mechanisms underlying this trait variation.

The metabolome as a biomarker of aging in Drosophila melanogaster

“…A set of 20 Drosophila Genetic Reference Panel (DGRP) (Mackay et al, 2012) strains were obtained from the Bloomington Drosophila Stock Center. All flies were maintained at low density on standard yeast–sucrose–glucose–cornmeal medium as described in (Harrison et al, 2020), in incubators at 24°C on a 12h: 12h light–dark cycle at ~50% humidity. All phenotypic assays and targeted metabolomic sampling were performed in two experimental blocks three months apart, with 11 DGRP strains in the first block and nine strains in the second.…”

“…These strains, which together offer a snapshot of current genetic variation within a single population, vary widely in diverse phenotypes (Mackay et al, 2012). Multiple studies have established extensive variation for metabolome profiles in the DGRP (Harrison et al, 2020; Hoffman et al, 2014), and recent work has mapped genetic variation for metabolite levels (Jin et al, 2020; Zhou et al, 2020). The fact that each strain within the DGRP is highly inbred allows us not only to obtain precise genotype‐specific estimates of lifespan and other demographic parameters but also to collect longitudinal measures of metabolome profiles.…”

Extending human healthspan and longevity: a symposium report

“…Studies in Drosophila have shown that the metabolome is a predictive biomarker of genotypes under stressful situations. 51 In a study of diet restriction in Drosophila, Promislow and colleagues showed that the treatment not only made flies live longer, but also reversed agerelated changes in the metabolome. 52 In a followup study of the effects of dietary restriction across almost 200 inbred strains of flies, Promislow and colleagues used metabolomic profiles to successfully predict whether diet restriction would increase or decrease lifespan.…”

Evolution of Natural Lifespan Variation and Molecular Strategies of Extended Lifespan

“…Evolution of gene expression is known to exhibit selective constraints [77,78], thereby supporting specific phenotypic outcomes such as changes in morphology [79] and lifespan [80]. Similarly, comparative studies on molecule abundance by metabolite profiling have been utilized to describe the genotype to phenotype relations in model organisms [81,82]. Accordingly, we aimed to explain lifespan differences among these natural populations of closely related yeast isolates by analyzing their endophenotype differences that include gene expression variation (transcriptomics) and differences in their metabolite levels (metabolomics).…”

“…In fact, gene expression variation has repeatedly been postulated to play a major role in adaptive evolution and phenotypic plasticity [74,75], as well as specific phenotypic outcomes such as changes in morphology [76] and lifespan [77]. Similarly, comparative studies of metabolite profiles have been utilized to describe the genotype to phenotype relations in model organisms [78,79]. Accordingly, we aimed to explain lifespan differences among these wild-derived yeast isolates by analyzing their gene expression variation (based on transcriptomics analyses) and differences in their metabolite levels (based on metabolomics analyses).…”