Biomimetic Sensors for the Senses: Towards Better Understanding of Taste and Odor Sensation

Electronic tongue for the simple and rapid determination of taste and odor compounds in water

Taste and odor (T&O) compounds present in natural water bodies could originate from algae. In this study, alga-generated compounds that can cause T&O issues in water, such as geosmin (GE), 2-Methylisoborneol (MIB), 2,4,6-Trichloroanisole (TCA), 2-Methylbenzofuran (MB), 2-Isopropyl-3-methoxypyrazine (IPMP), 2-Isobutyl-3-methoxypyrazine (IBMP), cis-3-Hexenyl acetate (HA), trans,trans-2,4-Heptadienal (HD), trans,cis-2,6-Nonadienal (ND), and trans-2-Decenal (DN), were determined through solid-phase microextraction coupled with gas chromatography/mass spectrometry (HS-SPME GC/MS) and electronic tongue (E-tongue), and the results from the two techniques were compared. Although HS-SPME GC/MS facilitates the detection and quantification of T&O compounds with high precision and accuracy, the sample preparation and handling is difficult and the analysis time (1 h) is longer than those of other analytical methods. E-tongue can be used as an alternative analytical method for water quality analysis and risk management because it enables controlled and rapid analysis (3 min) of T&O compounds in water at a low cost. Notably, principal component analysis indicated that E-tongue can discriminate and quantify eight T&O compounds at as low as 0.02 μg L-1 concentration. Further, partial least squares analysis confirmed that the sensor exhibits high sensitivity to concentration changes. The sensors with the highest variable importance in projection scores were determined to be SCS (1.39 and 1.38) for GE and MIB, CTS (1.34) for IPMP, CPS (1.33) for IBMP, AHS (1.42) for HA, ANS (1.22) for HD, and NMS (1.14 and 1.19) for ND and DN.

Management for stroke intelligent early warning empowered by big data

Global aging population, especially with the global pandemic outbreak of the Corona Virus Disease 2019 (COVID-19), has endangered human health security. Digital information technology through big data empowerment and intelligent application is widely considered a key element to solve the problems. Stroke is a life-threaten disorder. We studied individual health management and disease risk perception using human health assessment model and make full use of wearable wireless sensor, Internet of Things, big data, and Artificial Intelligence for potential risk monitoring and real-time stroke warning. We proposed an effective method of monitoring, early warning and rescue to improve the stroke treatment. The result shows that the health management empowered by big data can generate new opportunities and ideas to solve early detection and warning of stroke.

Differential sensing with arrays of de novo designed peptide assemblies

Differential sensing attempts to mimic the mammalian senses of smell and taste to identify analytes and complex mixtures. In place of hundreds of complex, membrane-bound G-protein coupled receptors, differential sensors employ arrays of small molecules. Here we show that arrays of computationally designed de novo peptides provide alternative synthetic receptors for differential sensing. We use self-assembling α-helical barrels (αHBs) with central channels that can be altered predictably to vary their sizes, shapes and chemistries. The channels accommodate environment-sensitive dyes that fluoresce upon binding. Challenging arrays of dye-loaded barrels with analytes causes differential fluorophore displacement. The resulting fluorimetric fingerprints are used to train machine-learning models that relate the patterns to the analytes. We show that this system discriminates between a range of biomolecules, drink, and diagnostically relevant biological samples. As αHBs are robust and chemically diverse, the system has potential to sense many analytes in various settings.

Field-Effect Sensors Using Biomaterials for Chemical Sensing

After millions of years of evolution, biological chemical sensing systems (i.e., olfactory and taste systems) have become very powerful natural systems which show extreme high performances in detecting and discriminating various chemical substances. Creating field-effect sensors using biomaterials that are able to detect specific target chemical substances with high sensitivity would have broad applications in many areas, ranging from biomedicine and environments to the food industry, but this has proved extremely challenging. Over decades of intense research, field-effect sensors using biomaterials for chemical sensing have achieved significant progress and have shown promising prospects and potential applications. This review will summarize the most recent advances in the development of field-effect sensors using biomaterials for chemical sensing with an emphasis on those using functional biomaterials as sensing elements such as olfactory and taste cells and receptors. Firstly, unique principles and approaches for the development of these field-effect sensors using biomaterials will be introduced. Then, the major types of field-effect sensors using biomaterials will be presented, which includes field-effect transistor (FET), light-addressable potentiometric sensor (LAPS), and capacitive electrolyte–insulator–semiconductor (EIS) sensors. Finally, the current limitations, main challenges and future trends of field-effect sensors using biomaterials for chemical sensing will be proposed and discussed.

Insect odorant receptor-based biosensors: Current status and prospects

Whilst the senses of vision and hearing have been successfully automated and miniaturized in portable formats (e.g. smart phone), this is yet to be achieved with the sense of smell. This is because the sensing challenge is not trivial as it involves navigating a chemosensory space comprising thousands of volatile organic compounds. Distinct aroma recognition is based on detecting unique combinations of volatile organic compounds. In natural olfactory systems this is accomplished by employing odorant receptors (ORs) with varying specificities, together with combinatorial neural coding mechanisms. Attempts to mimic the remarkable sensitivity and accuracy of natural olfactory systems has therefore been challenging. Current portable chemical sensors for odorant detection are neither sensitive nor selective, prompting research exploring artificial olfactory devices that use natural OR proteins for sensing. Much research activity to develop OR based biosensors has concentrated on mammalian ORs, however, insect ORs have not been explored as extensively. Insects possess an extraordinary sense of smell due to a repertoire of odorant receptors evolved to interpret olfactory cues vital to the insects' survival. The potential of insect ORs as sensing elements is only now being unlocked through recent research efforts to understand their structure, ligand binding mechanisms and development of odorant biosensors. Like their mammalian counterparts, there are many challenges with working with insect ORs. These include expression, purification and presentation of the insect OR in a stable display format compatible with an effective transduction methodology while maintaining OR structure and function. Despite these challenges, significant progress has been demonstrated in developing OR-based biosensors which exploit insect ORs in cells, lipid bilayers, liposomes and nanodisc formats. Ultrasensitive and highly selective detection of volatile organic compounds has been validated by coupling these insect OR display formats with transduction methodologies spanning optical (fluorescence) and electrical (field effect transistors, electrochemical impedance spectroscopy) techniques. This review summarizes the current status of insect OR based biosensors and their future outlook.

Biomimetic Nanostructure Platform for Cancer Diagnosis Based on Tumor Biomarkers

Biomarker discovery and its clinical use have attracted considerable attention since early cancer diagnosis can significantly decrease mortality. Cancer biomarkers include a wide range of biomolecules, such as nucleic acids, proteins, metabolites, sugars, and cytogenetic substances present in human biofluids. Except for free-circulating biomarkers, tumor-extracellular vesicles (tEVs) and circulating tumor cells (CTCs) can serve as biomarkers for the diagnosis and prognosis of various cancers. Considering the potential of tumor biomarkers in clinical settings, several bioinspired detection systems based on nanotechnologies are in the spotlight for detection. However, tremendous challenges remain in detection because of massive contamination, unstable signal-to-noise ratios due to heterogeneity, nonspecific bindings, or a lack of efficient amplification. To date, many approaches are under development to improve the sensitivity and specificity of tumor biomarker isolation and detection. Particularly, the exploration of natural materials in biological frames has encouraged researchers to develop new bioinspired and biomimetic nanostructures, which can mimic the natural processes to facilitate biomarker capture and detection in clinical settings. These platforms have substantial influence in biomedical applications, owing to their capture ability, significant contrast increase, high sensitivity, and specificity. In this review, we first describe the potential of tumor biomarkers in a liquid biopsy and then provide an overview of the progress of biomimetic nanostructure platforms to isolate and detect tumor biomarkers, including in vitro and in vivo studies. Capture efficiency, scale, amplification, sensitivity, and specificity are the criteria that will be further discussed for evaluating the capability of platforms. Bioinspired and biomimetic systems appear to have a bright future to settle obstacles encountered in tumor biomarker detection, thus enhancing effective cancer diagnosis.

Rational Control of Self-Recognition of Macroionic γ-Cyclodextrin by Host-Guest Interaction with Super-Chaotropic Borate Cluster Ions

We report a feasible method to control self-recognition during the self-assembly of a hydrophilic macroion, phosphate-functionalized γ-cyclodextrin (γ-CD-P), though host-guest interactions. We confirmed that γ-CD-P can form a host-guest complex with a super-chaotropic anion, namely the B₁₂ F₁₂ ^2- borate cluster, by using NMR spectroscopy and isothermal titration calorimetry. The loaded γ-CD-P, which has a higher charge density, can be distinguished from the uncomplexed γ-CD-P, leading to self-sorting behavior during the self-assembly process, confirmed by the formation of two types of individual supramolecular structures (R_h of ca. 57 nm and 18 nm, determined by light scattering) instead of hybrid structures in mixed dilute solution. This self-recognition behavior is accounted for by the difference in intermolecular electrostatic interactions arising from the loading.

Sensing Senses: Optical Biosensors to Study Gustation

The five basic taste modalities, sweet, bitter, umami, salty and sour induce changes of Ca²⁺ levels, pH and/or membrane potential in taste cells of the tongue and/or in neurons that convey and decode gustatory signals to the brain. Optical biosensors, which can be either synthetic dyes or genetically encoded proteins whose fluorescence spectra depend on levels of Ca²⁺, pH or membrane potential, have been used in primary cells/tissues or in recombinant systems to study taste-related intra- and intercellular signaling mechanisms or to discover new ligands. Taste-evoked responses were measured by microscopy achieving high spatial and temporal resolution, while plate readers were employed for higher throughput screening. Here, these approaches making use of fluorescent optical biosensors to investigate specific taste-related questions or to screen new agonists/antagonists for the different taste modalities were reviewed systematically. Furthermore, in the context of recent developments in genetically encoded sensors, 3D cultures and imaging technologies, we propose new feasible approaches for studying taste physiology and for compound screening.

Whisky tasting using a bimetallic nanoplasmonic tongue

Metallic nanostructures are ideal candidates for optical tongue devices thanks to their chemical stability, the sensitivity of their plasmonic resonance to environmental changes, and their ease of chemical-functionalization. Here, we describe a reusable optical tongue comprising multiplexed gold and aluminum nano-arrays: a bimetallic device which produces two distinct resonance peaks for each sensing region. Through specific modification of these plasmonic arrays with orthogonal surface chemistries, we demonstrate that a dual-resonance device allows us to halve sensor sizes and data-acquisition times when compared to single-resonance, monometallic devices. We applied our bimetallic tongue to differentiate off-the-shelf whiskies with >99.7% accuracy by means of linear discriminant analysis (LDA). This advance in device miniaturization, functionalization, and multiplexed readout indicates nanoplasmonic tongues will have future applications in chemical mixture identification in applications where portability, reusability, and measurement speed are key.

Statistical models discriminating between complex samples measured with microfluidic receptor-cell arrays

Data analysis for flow-based in-vitro receptomics array, like a tongue-on-a-chip, is complicated by the relatively large variability within and between arrays, transfected DNA types, spots, and cells within spots. Simply averaging responses of spots of the same type would lead to high variances and low statistical power. This paper presents an approach based on linear mixed models, allowing a quantitative and robust comparison of complex samples and indicating which receptors are responsible for any differences. These models are easily extended to take into account additional effects such as the build-up of cell stress and to combine data from replicated experiments. The increased analytical power this brings to receptomics research is discussed.

Ion Chromatographic Fingerprinting of STC-1 Cellular Response for Taste Sensing

Taste sensing is of great importance in both the pharmaceutical and foodstuff industries, and is currently mainly based on human sensory evaluation. Many approaches based on chemical sensors have been proposed, leading to the development of various electronic tongue systems. However, this approach is limited by the applied recognition methods, which do not consider natural receptors. Biorecognition elements such as taste receptor proteins or whole cells can be involved in the development of taste sensing biosensors usually equipped with various electrochemical transducers. Here, we propose a new approach: intestinal secretin tumor cell line (STC-1) chemosensory cells were applied for taste recognition, and their taste-specific cellular response was decoded from ion chromatographic fingerprints with the use of multivariate data processing by partial least squares discriminant analysis (PLS-DA). This approach could be useful for the development of various non-invasive taste sensing assays, as well as for studying taste transduction mechanisms in vitro.

Protein- and Peptide-Based Biosensors in Artificial Olfaction

Animals' olfactory systems rely on proteins, olfactory receptors (ORs) and odorant-binding proteins (OBPs), as their native sensing units to detect odours. Recent advances demonstrate that these proteins can also be employed as molecular recognition units in gas-phase biosensors. In addition, the interactions between odorant molecules and ORs or OBPs are a source of inspiration for designing peptides with tunable odorant selectivity. We review recent progress in gas biosensors employing biological units (ORs, OBPs, and peptides) in light of future developments in artificial olfaction, emphasizing examples where biological components have been employed to detect gas-phase analytes.