Larval density can be used to predict genetic modifiers of glucagon signaling in Drosophila melanogaster

TL;DR

This study uses fruit flies to identify genes that modify the effects of glucagon signaling, which could help in understanding obesity and developing new treatments.

Contribution

The study introduces a novel method using larval density to identify genetic modifiers of glucagon signaling in Drosophila.

Findings

THADA and AmyD are highlighted as key genes affecting larval density and metabolite levels.

Modifier genes were identified through a genome-wide association study using larval density.

Results from the density assay matched direct measurements of metabolite levels under different conditions.

Abstract

Obesity is a growing concern. 42.3% of people in the U.S were considered obese between 2017–2018. Much is still unknown about the genetic components that contribute to weight gain. In humans, the hormone glucagon is a major contributor to the body’s energy regulation as it signals for the breakdown of lipids. Treatments targeting the glucagon pathway have helped patients with both weight loss and appetite suppression. Understanding the genetic modifiers of glucagon signaling and its downstream pathways could enable the development of a wider variety of effective therapeutics. In this study, we blocked the glucagon pathway in Drosophila melanogaster by reducing the expression of the fly ortholog of the glucagon receptor (AKHR). We then crossed our model to the Drosophila Genetic Reference Panel (DGRP) and looked for natural variation in fat content. We used variation in larval density to identify candidate modifier genes through a genome-wide association study. We then tested these modifier genes by increasing or decreasing their expression in the AKHR model. We screened these candidates initially with the same density assay used in the original study to narrow down to four candidate genes that substantially impacted the density of the larvae: THADA, AmyD, GluRIIC, and CG9826. We further characterized these candidates using biochemical assays to analyze stored metabolites such as triglycerides, glucose, glycogen, and protein under control, high sugar, and high fat conditions to see if the larvae are resistant to environmental changes. Our results indicate consistency between the results of the density assay and direct measurement of metabolite levels. In particular, THADA and AmyD are highlighted as interesting genes for additional study. We hope to improve our understanding of the glucagon signaling pathway, obesity, and lipid metabolism. We also aim to provide candidate genes that can be regarded as future therapeutic targets.

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