Bioelectronic nose and its application to smell visualization

Skin-Integrated Wireless Odor Message Delivery Electronics for the Deaf-blind

Deaf-blindness limits daily human activities, especially interactive modes of audio and visual perception. Although the developed standards have been verified as alternative communication methods, they are uncommon to the nondisabled due to the complicated learning process and inefficiency in terms of communicating distance and throughput. Therefore, the development of communication techniques employing innate sensory abilities including olfaction related to the cerebral limbic system processing emotions, memories, and recognition has been suggested for reducing the training level and increasing communication efficiency. Here, a skin-integrated and wireless olfactory interface system exploiting arrays of miniaturized odor generators (OGs) based on melting/solidifying odorous wax to release smell is introduced for establishing an advanced communication system between deaf-blind and non-deaf-blind. By optimizing the structure design of the OGs, each OG device is as small as 0.24 cm3 (length × width × height of 11 mm × 10 mm × 2.2 mm), enabling integration of up to 8 OGs on the epidermis between nose and lip for direct and rapid olfactory drive with a weight of only 24.56 g. By generating single or mixed odors, different linked messages could be delivered to a user within a short period in a wireless and programmable way. By adopting the olfactory interface message delivery system, the recognition rates for the messages have been improved 1.5 times that of the touch-based method, while the response times were immensely decreased 4 times. Thus, the presented wearable olfactory interface system exhibits great potential as an alternative message delivery method for the deaf-blind.

Artificial Olfactory Biohybrid System: An Evolving Sense of Smell

The olfactory system can detect and recognize tens of thousands of volatile organic compounds (VOCs) at low concentrations in complex environments. Bioelectronic nose (B-EN), which mimics olfactory systems, is becoming an emerging sensing technology for identifying VOCs with sensitivity and specificity. B-ENs integrate electronic sensors with bioreceptors and pattern recognition technologies to enable medical diagnosis, public security, environmental monitoring, and food safety. However, there is currently no commercially available B-EN on the market. Apart from the high selectivity and sensitivity necessary for volatile organic compound analysis, commercial B-ENs must overcome issues impacting sensor operation and other problems associated with odor localization. The emergence of nanotechnology has provided a novel research concept for addressing these problems. In this work, the structure and operational mechanisms of biomimetic olfactory systems are discussed, with an emphasis on the development and immobilization of materials. Various biosensor applications and current developments are reviewed. Challenges and opportunities for fulfilling the potential of artificial olfactory biohybrid systems in fundamental and practical research are investigated in greater depth.

Harnessing insect olfactory neural circuits for detecting and discriminating human cancers

There is overwhelming evidence that presence of cancer alters cellular metabolic processes, and these changes are manifested in emitted volatile organic compound (VOC) compositions of cancer cells. Here, we take a novel forward engineering approach by developing an insect olfactory neural circuit-based VOC sensor for cancer detection. We obtained oral cancer cell culture VOC-evoked extracellular neural responses from in vivo insect (locust) antennal lobe neurons. We employed biological neural computations of the antennal lobe circuitry for generating spatiotemporal neuronal response templates corresponding to each cell culture VOC mixture, and employed these neuronal templates to distinguish oral cancer cell lines (SAS, Ca9-22, and HSC-3) vs. a non-cancer cell line (HaCaT). Our results demonstrate that three different human oral cancers can be robustly distinguished from each other and from a non-cancer oral cell line. By using high-dimensional population neuronal response analysis and leave-one-trial-out methodology, our approach yielded high classification success for each cell line tested. Our analyses achieved 76-100% success in identifying cell lines by using the population neural response (n = 194) collected for the entire duration of the cell culture study. We also demonstrate this cancer detection technique can distinguish between different types of oral cancers and non-cancer at different time-matched points of growth. This brain-based cancer detection approach is fast as it can differentiate between VOC mixtures within 250 ms of stimulus onset. Our brain-based cancer detection system comprises a novel VOC sensing methodology that incorporates entire biological chemosensory arrays, biological signal transduction, and neuronal computations in a form of a forward-engineered technology for cancer VOC detection.

Neurosensory Prosthetics: An Integral Neuromodulation Part of Bioelectronic Device

Bioelectronic medicines (BEMs) constitute a branch of bioelectronic devices (BEDs), which are a class of therapeutics that combine neuroscience with molecular biology, immunology, and engineering technologies. Thus, BEMs are the culmination of thought processes of scientists of varied fields and herald a new era in the treatment of chronic diseases. BEMs work on the principle of neuromodulation of nerve stimulation. Examples of BEMs based on neuromodulation are those that modify neural circuits through deep brain stimulation, vagal nerve stimulation, spinal nerve stimulation, and retinal and auditory implants. BEDs may also serve as diagnostic tools by mimicking human sensory systems. Two examples of in vitro BEDs used as diagnostic agents in biomedical applications based on in vivo neurosensory circuits are the bioelectronic nose and bioelectronic tongue. The review discusses the ever-growing application of BEDs to a wide variety of health conditions and practices to improve the quality of life.

Determination of quasi-primary odors by endpoint detection

It is known that there are no primary odors that can represent any other odors with their combination. Here, we propose an alternative approach: "quasi" primary odors. This approach comprises the following condition and method: (1) within a collected dataset and (2) by the machine learning-based endpoint detection. The quasi-primary odors are selected from the odors included in a collected odor dataset according to the endpoint score. While it is limited within the given dataset, the combination of such quasi-primary odors with certain ratios can reproduce any other odor in the dataset. To visually demonstrate this approach, the three quasi-primary odors having top three high endpoint scores are assigned to the vertices of a chromaticity triangle with red, green, and blue. Then, the other odors in the dataset are projected onto the chromaticity triangle to have their unique colors. The number of quasi-primary odors is not limited to three but can be set to an arbitrary number. With this approach, one can first find "extreme" odors (i.e., quasi-primary odors) in a given odor dataset, and then, reproduce any other odor in the dataset or even synthesize a new arbitrary odor by combining such quasi-primary odors with certain ratios.

Inkjet-Printed Colorimetric Paper-Based Gas Sensor Arrays for the Discrimination of Volatile Primary Amines with Amine-Responsive Dye-Encapsulating Polymer Nanoparticles

Arrays of gas sensors are of high interest for "electronic nose" applications. Here, we describe the fabrication of a colorimetric single-use gas sensor array made of paper allowing the discrimination of volatile primary amines based on their polarity. For this purpose, polymeric nanoparticles with different polarities containing an amine-sensitive chromogenic dye are deposited onto paper substrates by means of inkjet printing. Data processing is conducted by red-green-blue (RGB) color extraction, followed by principal component analysis (PCA) or agglomerative hierarchical clustering (AHC) analysis. The application to the discrimination of two cheese samples is demonstrated.

Membrane protein-based biosensors

This review highlights recent development of biosensors that use the functions of membrane proteins. Membrane proteins are essential components of biological membranes and have a central role in detection of various environmental stimuli such as olfaction and gustation. A number of studies have attempted for development of biosensors using the sensing property of these membrane proteins. Their specificity to target molecules is particularly attractive as it is significantly superior to that of traditional human-made sensors. In this review, we classified the membrane protein-based biosensors into two platforms: the lipid bilayer-based platform and the cell-based platform. On lipid bilayer platforms, the membrane proteins are embedded in a lipid bilayer that bridges between the protein and a sensor device. On cell-based platforms, the membrane proteins are expressed in a cultured cell, which is then integrated in a sensor device. For both platforms we introduce the fundamental information and the recent progress in the development of the biosensors, and remark on the outlook for practical biosensing applications.

Vapor detection and discrimination with a panel of odorant receptors

Olfactory systems have evolved the extraordinary capability to detect and discriminate volatile odorous molecules (odorants) in the environment. Fundamentally, this process relies on the interaction of odorants and their cognate olfactory receptors (ORs) encoded in the genome. Here, we conducted a cell-based screen using over 800 mouse ORs against seven odorants, resulting in the identification of a set of high-affinity and/or broadly-tuned ORs. We then test whether heterologously expressed ORs respond to odors presented in vapor phase by individually expressing 31 ORs to measure cAMP responses against vapor phase odor stimulation. Comparison of response profiles demonstrates this platform is capable of discriminating between structural analogs. Lastly, co-expression of carboxyl esterase Ces1d expressed in olfactory mucosa resulted in marked changes in activation of specific odorant-OR combinations. Altogether, these results establish a cell-based volatile odor detection and discrimination platform and form the basis for an OR-based volatile odor sensor.

Biomimetic “noses” have been proposed to replace trained animals for chemical detection. Here the authors select 31 mouse olfactory receptors (ORs), based on a large cell-based screen of >800 ORs against seven chemicals, to build an OR-based sensor able to discriminate structurally similar compounds.

Combining Two Selection Principles: Sensor Arrays Based on Both Biomimetic Recognition and Chemometrics

Electronic noses mimic smell and taste senses by using sensor arrays to assess complex samples and to simultaneously detect multiple analytes. In most cases, the sensors forming such arrays are not highly selective. Selectivity is attained by pattern recognition/chemometric data treatment of the response pattern. However, especially when aiming at quantifying analytes rather than qualitatively detecting them, it makes sense to implement chemical recognition via receptor layers, leading to increased selectivity of individual sensors. This review focuses on existing sensor arrays developed based on biomimetic approaches to maximize chemical selectivity. Such sensor arrays for instance use molecularly imprint polymers (MIPs) in both e-noses and e-tongues, for example, to characterize headspace gas compositions or to detect protein profiles. Other array types employ entire cells, proteins, and peptides, as well as aptamers, respectively, in multisensor systems. There are two main reasons for combining chemoselectivity and chemometrics: First, this combined approach increases the analytical quality of quantitative data. Second, the approach helps in gaining a deeper understanding of the olfactory processes in nature.

From Protein Features to Sensing Surfaces

Proteins play a major role in biosensors in which they provide catalytic activity and specificity in molecular recognition. However, the immobilization process is far from straightforward as it often affects the protein functionality. Extensive interaction of the protein with the surface or significant surface crowding can lead to changes in the mobility and conformation of the protein structure. This review will provide insights as to how an analysis of the physico-chemical features of the protein surface before the immobilization process can help to identify the optimal immobilization approach. Such an analysis can help to preserve the functionality of the protein when on a biosensor surface.

An overview of an artificial nose system

The present review describes recent advances in the development of an artificial nose system based on olfactory receptors and various sensing platforms. The kind of artificial nose, the production of olfactory receptors, the sensor platform for signal conversion and the application of the artificial nose system based on olfactory receptors and various sensing platforms are presented. The associated transduction modes are also discussed. The paper presents a review of the latest achievements and a critical evaluation of the state of the art in the field of artificial nose systems.

Applications and Advances in Bioelectronic Noses for Odour Sensing

A bioelectronic nose, an intelligent chemical sensor array system coupled with bio-receptors to identify gases and vapours, resembles mammalian olfaction by which many vertebrates can sniff out volatile organic compounds (VOCs) sensitively and specifically even at very low concentrations. Olfaction is undertaken by the olfactory system, which detects odorants that are inhaled through the nose where they come into contact with the olfactory epithelium containing olfactory receptors (ORs). Because of its ability to mimic biological olfaction, a bio-inspired electronic nose has been used to detect a variety of important compounds in complex environments. Recently, biosensor systems have been introduced that combine nanoelectronic technology and olfactory receptors themselves as a source of capturing elements for biosensing. In this article, we will present the latest advances in bioelectronic nose technology mimicking the olfactory system, including biological recognition elements, emerging detection systems, production and immobilization of sensing elements on sensor surface, and applications of bioelectronic noses. Furthermore, current research trends and future challenges in this field will be discussed.

The bioelectronic nose and tongue using olfactory and taste receptors: Analytical tools for food quality and safety assessment

Food intake is the primary method for obtaining energy and component materials in the human being. Humans evaluate the quality of food by combining various facets of information, such as an item of food's appearance, smell, taste, and texture in the mouth. Recently, bioelectronic noses and tongues have been reported that use human olfactory and taste receptors as primary recognition elements, and nanoelectronics as secondary signal transducers. Bioelectronic sensors that mimic human olfaction and gustation have sensitively and selectively detected odor and taste molecules from various food samples, and have been applied to food quality assessment. The portable and multiplexed bioelectronic nose and tongue are expected to be used as next-generation analytical tools for rapid on-site monitoring of food quality. In this review, we summarize recent progress in the bioelectronic nose and tongue using olfactory and taste receptors, and discuss the potential applications and future perspectives in the food industry.

Agonist Binding to Chemosensory Receptors: A Systematic Bioinformatics Analysis

Human G-protein coupled receptors (hGPCRs) constitute a large and highly pharmaceutically relevant membrane receptor superfamily. About half of the hGPCRs' family members are chemosensory receptors, involved in bitter taste and olfaction, along with a variety of other physiological processes. Hence these receptors constitute promising targets for pharmaceutical intervention. Molecular modeling has been so far the most important tool to get insights on agonist binding and receptor activation. Here we investigate both aspects by bioinformatics-based predictions across all bitter taste and odorant receptors for which site-directed mutagenesis data are available. First, we observe that state-of-the-art homology modeling combined with previously used docking procedures turned out to reproduce only a limited fraction of ligand/receptor interactions inferred by experiments. This is most probably caused by the low sequence identity with available structural templates, which limits the accuracy of the protein model and in particular of the side-chains' orientations. Methods which transcend the limited sampling of the conformational space of docking may improve the predictions. As an example corroborating this, we review here multi-scale simulations from our lab and show that, for the three complexes studied so far, they significantly enhance the predictive power of the computational approach. Second, our bioinformatics analysis provides support to previous claims that several residues, including those at positions 1.50, 2.50, and 7.52, are involved in receptor activation.