The T1R3 subunit of the sweet taste receptor is activated by D2O in transmembrane domain-dependent manner.

Deuterium oxide (D2O) is water in which the heavier and rare isotope deuterium replaces both hydrogens. We have previously shown that D2O has a distinctly sweet taste, mediated by the T1R2/T1R3 sweet taste receptor. Here, we explore the effect of heavy water on T1R2 and T1R3 subunits. We show that D2O activates T1R3-transfected HEK293T cells similarly to T1R2/T1R3-transfected cells. The response to glucose dissolved in D2O is higher than in water. Mutations of phenylalanine at position 7305.40 in the transmembrane domain of T1R3 to alanine, leucine, or tyrosine impair or diminish activation by D2O, suggesting a critical role for T1R3 TMD domain in relaying the heavy water signal.

Sweet taste of heavy water.

Hydrogen to deuterium isotopic substitution has only a minor effect on physical and chemical properties of water and, as such, is not supposed to influence its neutral taste. Here we conclusively demonstrate that humans are, nevertheless, able to distinguish D2O from H2O by taste. Indeed, highly purified heavy water has a distinctly sweeter taste than same-purity normal water and can add to perceived sweetness of sweeteners. In contrast, mice do not prefer D2O over H2O, indicating that they are not likely to perceive heavy water as sweet. HEK 293T cells transfected with the TAS1R2/TAS1R3 heterodimer and chimeric G-proteins are activated by D2O but not by H2O. Lactisole, which is a known sweetness inhibitor acting via the TAS1R3 monomer of the TAS1R2/TAS1R3, suppresses the sweetness of D2O in human sensory tests, as well as the calcium release elicited by D2O in sweet taste receptor-expressing cells. The present multifaceted experimental study, complemented by homology modelling and molecular dynamics simulations, resolves a long-standing controversy about the taste of heavy water, shows that its sweet taste is mediated by the human TAS1R2/TAS1R3 taste receptor, and opens way to future studies of the detailed mechanism of action.

The taste of KCl - What a difference a sugar makes.

Dramatic increase in NaCl consumption lead to sodium intake beyond health guidelines. KCl substitution helps reduce sodium intake but results in a bitter-metallic off-taste. Two disaccharides, trehalose and sucrose, were tested in order to untangle the chemical (increase in effective concentration of KCl due to sugar addition) from the sensory effects. The bitter-metallic taste of KCl was reduced by these sugars, while saltiness was enhanced or unaltered. The perceived sweetness of sugar, regardless of its type and concentration, was an important factor in KCl taste modulation. Though KCl was previously shown to increase the chemical activity of trehalose but not of sucrose, we found that it suppressed the perceived sweetness of both sugars. Therefore, sensory integration was the dominant factor in the tested KCl-sugar combinations.

Bitter or not? BitterPredict, a tool for predicting taste from chemical structure.

Bitter taste is an innately aversive taste modality that is considered to protect animals from consuming toxic compounds. Yet, bitterness is not always noxious and some bitter compounds have beneficial effects on health. Hundreds of bitter compounds were reported (and are accessible via the BitterDB http://bitterdb.agri.huji.ac.il/dbbitter.php ), but numerous additional bitter molecules are still unknown. The dramatic chemical diversity of bitterants makes bitterness prediction a difficult task. Here we present a machine learning classifier, BitterPredict, which predicts whether a compound is bitter or not, based on its chemical structure. BitterDB was used as the positive set, and non-bitter molecules were gathered from literature to create the negative set. Adaptive Boosting (AdaBoost), based on decision trees machine-learning algorithm was applied to molecules that were represented using physicochemical and ADME/Tox descriptors. BitterPredict correctly classifies over 80% of the compounds in the hold-out test set, and 70-90% of the compounds in three independent external sets and in sensory test validation, providing a quick and reliable tool for classifying large sets of compounds into bitter and non-bitter groups. BitterPredict suggests that about 40% of random molecules, and a large portion (66%) of clinical and experimental drugs, and of natural products (77%) are bitter.