Continuous Evolution Profiles for Electronic-Tongue-Based Analysis

Bio-Inspired Strategies for Improving the Selectivity and Sensitivity of Artificial Noses: A Review

Artificial noses are broad-spectrum multisensors dedicated to the detection of volatile organic compounds (VOCs). Despite great recent progress, they still suffer from a lack of sensitivity and selectivity. We will review, in a systemic way, the biomimetic strategies for improving these performance criteria, including the design of sensing materials, their immobilization on the sensing surface, the sampling of VOCs, the choice of a transduction method, and the data processing. This reflection could help address new applications in domains where high-performance artificial noses are required such as public security and safety, environment, industry, or healthcare.

A bioinspired in vitro bioelectronic tongue with human T2R38 receptor for high-specificity detection of N-C=S-containing compounds

Detection and identification of bitter compounds draw great attention in pharmaceutical and food industry. Several well-known agonists of specific bitter taste receptors have been found to exhibit anti-cancer effects. For example, N-C=S-containing compounds, such as allyl-isothiocyanates, have shown cancer chemo-preventive effects. It is worth noting that human T2R38 receptor is specific for compounds containing N-C=S moiety. Here, a bioinspired cell-based bioelctronic tongue (BioET) is developed for the high-specificity isothiocyanate-induced bitter detection, utilizing human Caco-2 cells as a primary sensing element and interdigitated impedance sensor as a secondary transducer. As an intestinal carcinoma cell line, Caco-2 endogenously expresses human bitter receptor T2R38, and the activation of T2R38 induces the changes of cellular morphology which can be detected by electric cell-substrate impedance sensing (ECIS). After configuration and optimization of parameters including timing of compound administration and cell density, quantitative bitter evaluation models were built for two well-known bitter compounds, phenylthiocarbamide (PTC) and propylthiouracil (PROP). The bitter specific detection of this BioET is inhibited by probenecid and U-73122, and is not elicited by other taste modalities or bitter ligands that do not activate T2R38. Moreover, by combining different computational tools, we designed a ligand-based virtual screening (LBVS) protocol to select ligands that are likely to activate T2R38 receptor. Three computationally predicted agonists of T2R38 were selected using the LBVS protocol, and the BioET presented response to the predicted agonists, validating the capability of the LBVS protocol. This study suggests this unique cell-based BioET paves a general and promising way to specifically detect N-C=S-containing compounds that can be used for pharmaceutical study and drug development.