Bimetallic bionic taste sensor for perception of the synergistic effect of umami substances

Multienzyme-Mediated Dual-Channel Magnetic Relaxation Switching Taste Biosensor (D-MRSTB) for Simultaneous Detection of Umami Compounds and Synergistic Enhancement in Food

Umami substances play a significant role in the evaluation of food quality, and their synergistic enhancement is of great importance in improving and intensifying food flavors and tastes. Current biosensors available for umami detection still confront challenges in simultaneous quantification of multiple umami substances and umami intensities. In this study, an innovative dual-channel magnetic relaxation switching taste biosensor (D-MRSTB) was developed for the quantitative detection of representative umami substances. The multienzyme signal of D-MRSTB specifically catalyzes the umami substances of interest to generate hydrogen peroxide (H2O2), which is then used to oxidate Fe2+ to Fe3+. Such a valence-state transition of paramagnetic ions was utilized as a magnetic relaxation signaling switch to influence the transverse magnetic relaxation time (T2) within the reaction milieu, thus achieving simultaneous detection of monosodium glutamate (MSG) and inosine 5'-monophosphate (IMP). The biosensor showed good linearity (R2 > 0.99) in the concentration range of 50-1000 and 10-1000 μmol/L, with limits of detection (LOD) of 0.61 and 0.09 μmol/L for MSG and IMP, respectively. Furthermore, the biosensor accurately characterized the synergistic effect of the mixed solution of IMP and MSG, where ΔT2 showed a good linear relationship with the equivalent umami concentration (EUC) of the mixed solution (R2 = 0.998). Moreover, the D-MRSTB successfully achieved the quantitative detection of umami compounds in real samples. This sensing technology provides a powerful tool for achieving the detection of synergistic enhancement among umami compounds and demonstrates its potential for application in the food industry.

A novel biomimetic electrochemical taste-biosensor based on conformational changes of the taste receptor

Taste sensor, a useful tool which could detect and identify thousands of different chemical substances in liquid environments, has attracted continuous concern from beverage and foodstuff industry and its consumers. Although many taste sensing methods have been extensively developed, the assessment of tastant content remains challenging due to the limitations of sensor selectivity and sensitivity. Here we present a novel biomimetic electrochemical taste-biosensor based on bioactive sensing elements and immune amplification with nanomaterials carrier to address above concerns, while taking sweet taste perception as a model. The proposed biosensor based on ligand binding domain (T1R2 VFT) of human sweet taste receptor protein showed human mimicking character and initiated the application of immune recognition in gustation biosensor, which can precisely and sensitively distinguish sweet substances against other related gustation substances with detection limit of 5.1 pM, far less than that of taste sensors without immune amplification whose detection limit was 0.48 nM. The performance test demonstrated the biosensor has the capacity of monitoring the response of sweet substances in real food environments, which is crucial in practical. This biomimetic electrochemical taste-biosensor can work as a new screening platform for newly developed tastants and disclose sweet perception mechanism.

From Molecular Dynamics to Taste Sensory Perception: A Comprehensive Study on the Interaction of Umami Peptides with the T1R1/T1R3-VFT Receptor

The research on the umami receptor-ligand interaction is crucial for understanding umami perception. This study integrated molecular simulations, sensory evaluation, and biosensor technology to analyze the interaction between umami peptides and the umami receptor T1R1/T1R3-VFT. Molecular dynamics simulations were used to investigate the dissociation process of seven umami peptides with the umami receptor T1R1/T1R3-VFT, and by calculating the potential mean force curve using the Jarzynski equation, it was found that the binding free energy of umami peptide is between -58.80 and -12.17 kcal/mol, which had a strong correlation with the umami intensity obtained by time intensity sensory evaluation. Through correlation analysis, the dissociation rate constants (0.0126-0.394 1/s) of umami peptides were found to have a great impact on umami perception. The faster the dissociation rate of umami peptides from receptors, the stronger the perceived intensity of the umami taste. This research aims to elucidate the relationship between the umami peptide-receptor interaction and umami perception, providing theoretical support for the exploration of umami perception mechanisms.

TastePeptides-EEG: An Ensemble Model for Umami Taste Evaluation Based on Electroencephalogram and Machine Learning

In the field of food, the sensory evaluation of food still relies on the results of manual sensory evaluation, but the results of human sensory evaluation are not universal, and there is a problem of speech fraud. This work proposed an electroencephalography (EEG)-based analysis method that effectively enables the identification of umami/non-umami substances. First, the key features were extracted using percentage conversion, standardization, and significance screening, and based on these features, the top four models were selected from 19 common binary classification algorithms as submodels. Then, the support vector machine (SVM) algorithm was used to fit the outputs of these four submodels to establish TastePeptides-EEG. The validation set of the model achieved a judgment accuracy of 90.2%, and the test set achieved a judgment accuracy of 77.8%. This study discovered the frequency change of α wave in umami taste perception and found the frequency response delay phenomenon of the F/RT/C area under umami taste stimulation for the first time. The model is published at www.tastepeptides-meta.com/TastePeptides-EEG, which is convenient for relevant researchers to speed up the analysis of umami perception and provide help for the development of the next generation of brain-computer interfaces for flavor perception.