A new metabolic model ofDrosophila melanogasterand the integrative analysis of Parkinson’s disease

Abstract

High conservation of the disease-associated genes between flies and humans facilitates the common use ofDrosophila melanogasterto study metabolic disorders under controlled laboratory conditions. However, metabolic modeling studies are highly limited for this organism. We here report a comprehensively curated genome-scale metabolic network model ofDrosophilausing an orthology-based approach. The gene coverage and metabolic information of the draft model derived from a reference human model were expanded viaDrosophila-specific KEGG and MetaCyc databases, with several curation steps to avoid metabolic redundancy and stoichiometric inconsistency. Furthermore, we performed literature-based curations to improve gene–reaction associations, subcellular metabolite locations, and various metabolic pathways. The performance of the resultingDrosophilamodel (8,230 reactions, 6,990 metabolites, and 2,388 genes), iDrosophila1 (https://github.com/SysBioGTU/iDrosophila), was assessed using flux balance analysis in comparison with the other currently available fly models leading to superior or comparable results. We also evaluated the transcriptome-based prediction capacity of iDrosophila1, where differential metabolic pathways during Parkinson’s disease could be successfully elucidated. Overall, iDrosophila1 is promising to investigate system-level metabolic alterations in response to genetic and environmental perturbations.

Identification of high sugar diet-induced dysregulated metabolic pathways in muscle using tissue-specific metabolic models in Drosophila

“…The results of our metabolic network analysis not only recapitulated known metabolic functions of individual tissues, but also revealed distinct metabolic network structures across tissues. This information is valuable as currently available GEMs for Drosophila , such as Fruitfly1 25 , FlySilico 23 , and iDrosophila 24 , are not tissue-specific, used for larvae, or used for a specific brain disease model, respectively. Furthermore, while previous GEMs in Drosophila did not consider enzyme constraints, we integrated enzyme kinetics and abundances into each tissue-specific GEM, revealing maximum rate distributions across tissues.…”

“…In Drosophila, several GEMs have been generated to analyze metabolic perturbations in silico. For instance, FlySilico was developed to identify essential amino acids that control larval growth rate 23 and iDrosophila was built to evaluate a fly model of Parkinson’s disease 24 . Moreover, Fruitfly1 was reconstructed as a comprehensive generic model based on ortholog and biochemical reactions from the KEGG database 25 .…”

Physiological constraints limiting the growth ofDrosophilalarvae

“…(iii) The ATP yield of different carbon sources for human (Swainston et al, 2016). Moreover, FBA was already successfully used to understand the development and environmental impacts on Drosophila melanogaster larvae and flies by examining resource allocation, impact of altered growth conditions and the resulting impact on metabolic fluxes (Coquin et al, 2008; Feala et al, 2009; Schönborn et al, 2019; Cesur et al, 2023).…”