How to use the development of individual Drosophila larvae as a metabolic sensor
Publikation: Beitrag in Fachzeitschrift › Forschungsartikel › Beigetragen › Begutachtung
Beitragende
Abstract
Metabolic research is a challenge because of the variety of data within experimental series and the difficulty of replicating results among scientific groups. The fruit fly, Drosophila melanogaster, is a cost-effective and reliable pioneer model to screen dietary variables for metabolic research. One of the main reasons for problems in this field are differences in food recipes, diet-associated microbial environments and the pharmacokinetic behavior of nutrients across the gut-blood barrier. To prevent such experimental shortcomings, a common strategy is to pool scores of subjects into one sample to create an average statement. However, this approach lacks information about the biological spread and may provoke misleading interpretations. We propose to use the developmental rate of individual Drosophila larvae as a metabolic sensor. To do so, we introduce here a 96-well plate-based assay, which allows screening for multiple variables including food quality, microbial load, and genetic differences. We demonstrate that on a diet that is rich in calories, pupation is sensitive to the variation of dietary lipid compounds and that genotypes considered as wild-types/controls produce different developmental profiles. Our platform is suited for later automation and represents a potent high-throughput screening tool for the pharmacology and food industry. If used systematically, our assay could become a powerful reference tool to compare the quality of used dietary configurations with published benchmark recipes.
Details
Originalsprache | Englisch |
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Aufsatznummer | 104095 |
Fachzeitschrift | Journal of Insect Physiology |
Jahrgang | 126 |
Publikationsstatus | Veröffentlicht - Okt. 2020 |
Peer-Review-Status | Ja |
Externe IDs
PubMed | 32783958 |
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Schlagworte
ASJC Scopus Sachgebiete
Schlagwörter
- Development, Diet, Drosophila, Genotypes, Metabolism, Nutrition