Cholesterol taste avoidance in Drosophila melanogaster
Nhuchhen Pradhan, R.; Montell, C.; Lee, Y.
Show abstract
The question as to whether animals taste cholesterol taste is not resolved. This study investigates whether the fruit fly, Drosophila melanogaster, is capable of detecting cholesterol through their gustatory system. We found that flies are indifferent to low levels of cholesterol and avoid higher levels. The avoidance is mediated by gustatory receptor neurons (GRNs), demonstrating that flies can taste cholesterol. The cholesterol responsive GRNs comprise a subset that also respond to bitter substances. Cholesterol detection depends on five ionotropic receptor (IR) family members, and disrupting any of these genes impairs the flies ability to avoid cholesterol. Ectopic expressions of these IRs in GRNs reveals two classes of cholesterol receptors, each with three shared IRs and one unique subunit. Additionally, expressing cholesterol receptors in sugar-responsive GRNs confers attraction to cholesterol. This study reveals that flies can taste cholesterol, and that the detection depends on IRs in GRNs.
Matching journals
The top 1 journal accounts for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- The TWK-26/KCNK3 potassium channel and FLR-4 protein kinase coordinate nutrient absorption in the C. elegans intestine 96%
- Developmental history modulates adult olfactory behavioral preferences via regulation of chemoreceptor expression in C. elegans 95%
- Strong GAL4 expression compromises Drosophila fat body function 95%
Similar papers in this journal
- Nuclear receptor NHR-49 promotes peroxisome proliferation to compensate for aldehyde dehydrogenase deficiency in C. elegans 95%
- α-Phenylalanyl tRNA synthetase competes with Notch signaling through its N-terminal domain 95%
- Neuronal SKN-1B Modulates Nutritional Signalling Pathways and Mitochondrial Networks to Control Satiety 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.