Computational tools for metabolic analysis in flies

lab animal Research highlights Metabolomics https://doi.org/10.1038/s41684-026-01706-9 Computational tools for metabolic analysis in flies Check for updates Genome-scale metabolic models (GEMs) are computational representations of an organism’s entire metabolic network. GEMs are built using a combination of automated approaches and manual curation based on the available literature and experimental data. Although generic GEMs, such as FlySilico, have been recently developed to predict metabolic networks in Drosophila—a powerful model for human metabolic diseases—they lack the resolution required for tissue-specific metabolic analysis. A new study reports the development of 32 adult Drosophila tissue-specific GEMs, enabling systematic comparisons of metabolic network structures across individual tissues. As proof of concept, the researchers used this framework to identify high sugar diet (HSD)-induced metabolic dysregulation in muscle. Lab Animal | Volume 55 | March 2026 | 72 The team reconstructed the different GEMs by integrating the generic Fruitfly3 GEM with pseudo-bulk single-nuclei transcriptomics data from 32 individual tissues in the Fly Cell Atlas. Using the framework, they identified metabolic differences and similarities across different tissues in Drosophila, including muscles, gut, fat body and neurons. Then, they performed metabolomics and pathway analysis on four dissected Drosophila regions (head, containing neuronal and glial cells; thorax, containing muscle cells; gut, containing hind-gut/enteroendocrine cells; and abdomen) and compared the data to the tissue-specific GEMs. They found that the experimental results closely matched model-predicted pathway activity, notably in muscle and fat body. Finally, to demonstrate the utility in disease modeling, they applied muscle-GEM to investigate HSD-induced metabolic dysregulation. Constraint-based semi-quantitative flux and sensitivity analyses revealed altered NAD(H)-dependent reactions and distributed control of glycolytic flux, including GAPDH. These predictions were validated with in vivo 13 C-glucose isotope tracing experiments. Together, these GEMs provide a quantitative, systems-level framework that complements existing Drosophila tools and advances metabolic research in flies. Alexandra Le Bras Original reference: Moon, S.J. et al. Nat. Commun. https://doi.org/10.1038/s41467-026-68395-3 (2026) 72  (...truncated)