Recent achievements in electronic tongue and bioelectronic tongue as taste sensors

Accepted Manuscript Title: Recent Achievements in Electronic Tongue and Bioelectronic Tongue as Taste Sensors Author: Da Ha Ning Hu Qiyong Sun Kaiqi Su Hao Wan Haibo Li Ning Xu Fei Sun Ping Wang PII: DOI: Reference:

S0925-4005(14)01163-0 http://dx.doi.org/doi:10.1016/j.snb.2014.09.077 SNB 17453

To appear in:

Sensors and Actuators B

Received date: Revised date: Accepted date:

12-5-2014 7-8-2014 22-9-2014

Please cite this article as: D. Ha, N. Hu, Q. Sun, K. Su, H. Wan, H. Li, N. Xu, F. Sun, P. Wang, Recent Achievements in Electronic Tongue and Bioelectronic Tongue as Taste Sensors, Sensors and Actuators B: Chemical (2014), http://dx.doi.org/10.1016/j.snb.2014.09.077 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Recent Achievements in Electronic Tongue and Bioelectronic Tongue as Taste Sensors

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Da Ha+, Ning Hu+, Qiyong Sun, Kaiqi Su, Hao Wan, Haibo Li, Ning Xu, Fei Sun, Ping Wang*

Biosensor National Special Laboratory, Key Laboratory for Biomedical Engineering

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Hangzhou, P. R. China, 310027

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of Education Ministry, Department of Biomedical Engineering, Zhejiang University,

These authors contributed equally to this work.

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* Corresponding author: E-mail: [email protected] Tel: +86 571 87952832.

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Abstract This review presents recent achievements concerning work with electronic tongue

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(ET) and bioelectronic tongue (BioET) for taste assessment. These two emerging

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analytical technologies can be designed as taste sensors, which simulate the taste

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detection modality of human tongue by means of electrochemical sensors or biosensors array. For electronic tongue, the potentiometric and voltammetric types are

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mainly discussed together with applications in food and pharmaceutical analysis. Enzymatic and gustatory receptor-based biosensors towards bioelectronic tongues are

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presented.

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Keywords: Electronic tongue, Bioelectronic tongue, Potentiometry, Voltammetry,

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Enzymatic biosensor, Gustatory receptor-based biosensor, Taste assessment

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1. Introduction In taste assessment in the food and pharmaceutical industries, sensory tests are

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generally implemented by human panelists. The human tongue which contains taste

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receptors, in the form of 10000 taste buds of 50-100 taste cells each [1], can generate

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unique signal patterns of a variety of substances to the human brain. Then the brain interprets these signals and makes a judgment or classification to identify the

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substances concerned, based on the experiences or neural network pattern recognition. However, the human-panel method is problematic due to its low objectivity and

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reproducibility, as well as the potential stress imposed onto the panelists. Use of taste sensors is expected to largely improve this situation. Electronic tongue and

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bioelectronic tongue, known as two promising tools for the taste assessment of foodstuffs, can mimic the human taste sensors and their communication with the

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human brain, thereby making themselves analytical instruments that artificially and effectively reproduce the taste sensation. According to the IUPAC technical report, an electronic tongue is defined as “a

multisensory system, which consists of a number of low-selective sensors and uses advanced mathematical procedures for signal processing based on the Pattern Recognition (PARC) and/or multivariate data analysis” [2]. Therefore, the electronic tongue can be an analytical tool including an array of non-specific, poorly selective chemical

sensors

with

partial

specificity

(cross-selectivity),

coupled

with

chemometric processing, for recognizing the qualitative and quantitative composition 3

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of multispecies solutions. Various sensing methodology can be used in electronic tongue, such as electrochemical methods (e.g., potentiometry or voltammetry), optical methods, mass change sensing techniques based on some principles like

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quartz-crystals. Unlike the other analytical methods, electronic tongues only present a

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digital fingerprint of the food stuff, without acquiring data on the nature of the

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compounds. The distorted information due to overlapping or interference signals can be operated by chemometric tools. The data processing algorithms involved mainly

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include Principal Component Analysis (PCA) which is mostly used in identification/classification for qualitative purpose, Partial Least Squares (PLS) which

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is mainly used in multidetermination for quantitative purpose, Artificial Neural Networks (ANN) which is a massively parallel computing method, especially suitable

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for non-linear sensor signals and extremely related to human pattern recognition. Recently the concept of bioelectronic tongue is emerging and has been used for

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taste evaluation. This one is characterized by including one or several biosensing elements into the sensor array. To be designed as a biosensor, the sensor’s recognition should be of biological origin, such as enzymes, antigens, antibodies, receptor proteins, cells or tissues. Although bioelectronic tongues have been applied to some taste characteristics and selective detection of food components, it is worth mentioning it is still in the early stage and much fewer applications to the assessment of the taste or quality of food are reported. Nevertheless, bioelectronic tongue still shows a promising perspective for the achievement of this goal. This review lists the recent achievements concerning work with electronic 4

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tongue and bioelectronic tongue for taste assessment. The sense of taste may include two meanings. One aspect refers to the five basic tastes of the tongue, namely sourness, saltiness, bitterness, sweetness and umami. The other aspects refer to the

perceptions.

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2. Development of various electronic tongue

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components or additives of edible stuffs which provide human tongue respective

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2.1 Potentiometric sensors

Potentiometric sensors were utilized in the first application of sensor arrays for

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multicomponent analysis of liquid, and they still remain the most widely used category in e-tongue system. The main advantages of potentiometric sensors such as

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ion-selective electrodes (ISEs) are their well-known characteristics such as low cost,

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simple set-up and easy fabrication. On the other hand, the temperature dependence

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and the absorption of solution components which may affect the membrane potential lead to their weakness.

Legin et al. proposed a potentiometric e-tongue system comprising a group of

ISEs based on PVC membranes or chalcogenide glass. The system has served for the discrimination of beer, soft drinks, juice, tea, coffee, mineral water and wine [3-5]. The research on quantifications of tastes provided discrimination between bitter, sweet and salty substances, and discrimination between substances eliciting the same taste, quantity and content in pharmaceutical products [6]. In a recent study [7], A. Rudnitskaya et al. employed an e-tongue comprising 17 potentiometric chemical 5

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sensors for the quantification of bitterness in red wines. It was found that bitter-tasting wines had higher concentrations of phenolic compounds (catechin, epicate-chin, gallic and caffeic acids and quercetin) than non-bitter wines. The data sets allowed

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classifying wines according to the existence of bitter taste with correct classification

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rate of 94% for the ET system. Calibration model calculated using ET data allowed

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good quantitative prediction of the bitterness intensity with RESEP of 2% and MRE of 6%. In another study [8], the ET capability of predicting Maderia wine age with

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good accuracy (1.8 years) as well as quantification of some organic acids and phenolic compounds was demonstrated. Similar work can be found in other recent

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literatures for analysis of beers according to their taste evaluation [9, 10]. In order to assess the bitter taste of structurally diverse active pharmaceutical ingredients (APIs),

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a potentiometric multisensory system was employed for bitterness quantification [11]. The 3wayPLS regression models were constructed from the yielded 3 way data array

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(samples × sensors × pH levels) with both human panel and rat model reference data.

It was demonstrated that the E-Tongue could be used for the artificial assessment of bitter taste of APIs, exhibiting average relative errors of 16% in terms of human panel bitterness score and 25% in terms of inhibition values form in vivo rat model data.

Figure 1

Ever since the first multi-sensor system for liquid analysis based on a 6

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non-specific sensor approach was produced by Toko et al. in 1990, the so-called “taste sensor” has been further developed towards advanced direction, with improvements leading to successful application in taste evaluation in food industry. The suggested

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potentiometric taste sensor consisted of eight sensors with polymeric membranes

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containing PVC, a plasticizer such as DOPP (dioctylphenyl-phosphonate) and active

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substances (artificial lipids such as TOMA (trioctylmethylammonium chloride), oleic acid and gallic acid), which were assumed to more specifically mimic the functions of

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human taste receptors. The diagram of taste sensing system is presented in Fig. 1(a). Recently, based on this taste sensor system, the potentiometric responses of the

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lipid/polymer membranes to saltiness [12], bitterness [13], sweetness [14, 15] and umami [16] have been investigated. The measuring procedure of taste evaluation by

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this sensor system can be described as following: firstly, chemical substances with unknown taste are detected by taste sensor with global selectivity and high correlation

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to human sensory score. Then, sensor outputs are collected and converted to 11 types `of taste information. Finally, the combination of taste information, by means of radar chart [Fig. 1(b)] or taste map is illustrated to provide satisfactory results for taste qualities. The taste sensors have been extensively applied in food manufacturing [17-20] and evaluation of taste suppression [21-24]. In recent research, the development of the taste sensor has been promoted towards the concept of portable setup [25], high-throughput chip [26] and miniaturization [27]. The ion-selective field effect transistor (ISFET) and the light-addressable potentiometric sensor (LAPS) which was derived from ISFET are other sensor basis 7

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for electronic tongue construction. Based on semiconductor physics and microfabrication technology, these silicon-based sensors are easier to realize miniaturization and provide an effective platform for simultaneous detection of

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several compounds. An e-tongue employing an array formed by ISFET potentiometric

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sensors was developed by L. Moreno et al. They used large area ISFET chips,

encapsulated in a single device, where photocurable polyurethane membranes

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sensitive to K+, Na+, Ca2+ and Cl- were prepared, allowing for a six-channel device

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after incorporation of pH and redox potential elements. The device has been used for the identification of mineral waters [28], grape juice and wine samples [29]. Very

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recently, K. Maehashi has fabricated a highly sensitive and selective K+ sensor by modifying grapheme FETs with valinomycin [30], as shown in Fig. 2(a). The

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elaborated sensor showed sensitivity over a wide concentration range from 10 nM to 1.0 mM [Fig. 2(b)], with no apparent interference of additional Na ions. An ultrathin

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InN ISFET was fabricated and characterized to show a gate sensitivity of 58.3 mV/pH in the pH range of 2-12, with the response time of less than 10 s [31]. Fig. 2(c) shows the schematic section and physical top-view of InN-ISFET. The current variation ratio was 4.0%/pH and the resolution of detection was less than 0.03 pH [Fig. 2(d)]. With regard to the LAPS sensors, polymer membranes [32] or chalcogenide glass membranes [33, 34] containing specific receptor molecules can be coupled with them for simultaneous detection of heavy metals.

Figure 2 8

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2.2 Voltammetric/amperometric sensors

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Voltammetric/amperometric sensors are also widely used in E-tongue systems, owing to their merits of high selectivity, high signal-to-noise ratio, low detection limit

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and various modes of multicomponent measurement. Moreover, by surface

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modification with various chemosensitive materials, the electrodes exhibit various sensitivity and selectivity towards diverse species. However, their applicability is

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limited to redox-active substances and they share the same problem of temperature

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dependence and large surface alteration leading to sensor response drifts. For amperometric E-tongues there are three main classes including noble metal,

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conducting polymer and phtalocyanine film. The voltammetric E-tongue composing

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an array of noble metal working electrodes has been developed and applied to the

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analysis of different foodstuffs by Winquist et al. [35-37]. Noble metals, such as platinum, gold, iridium, palladium, and rhodium were selected for the array and two types of voltammetry, namely small-amplitude pulse voltammetry (SAPV) and large-amplitude pulse voltammetry (LAPV) were investigated. The most informative data points were extracted during the data processing and utilized for calibration and recognition. Different techniques including SAPV, LAPV and staircase voltammetry has been used for characterization of tea [38], detergents [39], juices [35] and milk [40]. Moreover, the e-tongue has been utilized to detect various species of molds growing in water environment [41], different microbial species [42], and quality of drinking water [43]. Tian et al. developed the ET system incorporated several metallic 9

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working electrodes (platinum, gold, palladium, titanium, nickel, etc.), with the combination of multifrequency large amplitude pulse voltammetry (MLAPV). This system could successfully classify the six Chinese distilled spirits and seven Longjing

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teas in different frequency segments [44]. Recently, micro-fabrication techniques were

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used to prepare a sensor array for construction of voltammetric e-tongue by depositing

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Au, Pt, It, Rh on a silicon wafer [45].

To obtain cross-selectivity and better performance, various materials such as

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polymers, graphite-epoxy, phthalocyanines and doping agents have been used as coating membranes for sensor design[46-48]. For instance, E-tongue with

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modification of conducting polymers such as polypyrrole and polyaniline showed a variation of conductivity with adsorption of different analytes [49]. E-tongues based

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on conducting polymers have been used to evaluate bitterness [50], as well as sweet, salty, acid, and astringent tastes [51]. Xavier Cetó and co-workers developed a novel

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E-tongue containing five modified graphite-epoxy electrodes for the analysis of cava wines [48]. In general, the advantage of conducting polymers is the rapid adsorption/desorption and partial selectivity through modifying the dopant of the polymer.

On the other hand, voltammetric sensors chemically modified with

phthalocyanines have also been successfully utilized in electronic tongues. Sensing areas composed of different phthalocyanine derivatives can offer significant cross-selectivity owing to their versatility, varied ion-binding and electrocatalytic properties. Apart from this, another benefit of phthalocyanines as sensing materials is 10

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that they can be modified by different techniques, such as the carbon paste technique and Langmuir-Blodgett technique, thereby providing different structures with different properties. A sensor array based on voltammetric electrodes with surface

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modification of bisphthalocyanines has been used to discriminate between the

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samples of five basic tastes [52]. Similarly, based on this system, bitter substances

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including MgCl2, quinine, and four phenolic compounds which are the main responsible of the bitterness detected in olive oils were investigated [50]. In another

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study, antioxidants usually present in foods have been discriminated by a sensor array modified with bisphthalocyanines and heteroleptic derivatives [53]. Sensor arrays

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based on phthalocyanines have been extensively applied in the analysis of food and beverages, particularly in the field of wines, for the reason that the objective analytes

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such as ions and electroactive materials lead a crucial role in the organoleptic properties of wines. For example, this type of voltammetric e-tongue has been able to

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discriminate red wines with different organoleptic characteristics [54] and antioxidant capabilities [55]. Multisensors based on phthalocyanines have also been successfully used in discrimination of different olive oils [56], beers of different qualities [57] or in evaluation of the fish freshness [58] through the level of biogenic amines. 2.3 Other variants of electrochemical sensors Regarding the sensor array used in the design of e-tongues, a wide variety of other chemical sensors can be employed. For example, other electrochemical sensors including impedimetric sensors[59-61] and conductimetric sensors, optical sensors[62, 63], piezoelectric sensors such as surface acoustic wave (SAW) device and quartz 11

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crystal microbalance (QCM) device can be used as the sensor basis (summarized in Table 1.). Impedemic e-tongues have been used for different analytes such as cations (K+, Na+, NH4+) [64]. In another study, the sensors were utilized to monitor the

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representatives of the five basic tastes, namely sodium chloride (saltiness), citric acid

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(sourness), glucose (sweetness), glutamic acid (umami), and sodium dehydrocholate

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(bitterness) [65]. QCM sensors modified by dioctadecyldimethylammonium poly (styrene sulfonate) was used to predict bitterness intensity of beer [66], while QCM

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sensor coated with dimyristoylphosphatidylethanolamin was used for measuring body, smoothness, bitterness, and astringency of beer [67, 68]. A miniaturized taste sensing

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system based upon a dual shear horizontal surface acoustic wave (SH-SAW) device was designed for distinguish between liquids of different basic taste [69]. After the

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data processing of PCA, this device could classify correctly four basic tastes of sour,

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salt, bitter and sweet, without a selective biological or chemical coating.

3. Development of bioelectronic tongue Basically, output signals of electronic tongues are analyzed by pattern

recognition techniques composed of an array of semiselective recognition elements. Even with technological advances and promising results, these sensors still cannot mimic the biological features of human tongue with regards to identifying elusive analytes in complicated mixtures. In this case, bioelectronic tongues can provide taste signals triggered by the binding activities between selective taste receptors and tastants, making it possible to develop artificial taste sensors that more closely mimic human taste system. To be considered as a bioelectronic tongue, the sensor’s 12

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recognition component should be of biological origin, namely enzymes, whole cells, tissues, receptors or antibodies. Table 2 summarized different types of bioelectronic tongue including biomolecule type, transducer part, biological recognition component

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and target molecules. From the perspective of basic mechanism, the signal

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transduction in biological system involves a series of biochemical reactions leading to

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the transport of electrons, ions or molecules. Although one would consider that bioelectronic tongues usually involve very selective, almost specific detection,

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biosensors can present response to a group of specific substances. Thus the bioelectronic tongues always need to be utilized with the help of advanced statistical

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methods for more accurate results. The synergistic coupling of biotechnology and electronics has promoted the development of biosensors[70]. Recently, the usage of

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nanotechnology in biosensor which could enhance sensor selectivity and sensitivity

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has been of interest to the researchers [71-73]. 3.1 Enzymatic biosensor

Enzymatic biosensors have emerged as a promising tool for qualitative and

quantitative analysis of a variety of target analytes in environmental monitoring, food quality control and pharmaceutical industry. The most widely used enzyme-based biosensors are those designed for glucose, lactate, glutamate, urea, creatinine and cholesterol. Gutes et al. [74] have developed a voltammetric BioET grouping different glucose biosensors, formed by epoxy-graphite biocomposites with glucose oxidase enzyme and different metal catalysts to generate differentiated signals. This system 13

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has been successfully utilized for the simultaneous detection of glucose and ascorbic acid. Based on FET sensors, aptamers and single-walled carbon nanotubes (SWNT) were used for surface modification, resulting in a system with capability of real-time

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monitoring of thrombin, at concentrations as low as 7 pM [75], as shown in Fig. 3. A

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novel enzymatic FET was presented by Premanode, in which creatininase, creatinase

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and urease were modified on the transistor for real-time detection of creatinine and urea [76]. Braeken [77] reported another enzymatic FET with surface coating of

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glutamate oxidase layers. This sensor exhibited high sensitivity and long-term stability towards the determination of glutamate. For the detection of four wastewater

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samples of different treatment qualities, namely untreated, alarm, alert and normal, an amperometric bioelectronic tongue with enzymatic modification was developed [78].

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Seven out of eight platinum electrodes of the array were modified with four different enzymes; tyrosinase, horseradish peroxidase, acetyl cholinesterase and butyryl

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cholinesterase.

Figure 3

For the detection of urea, a urea biosensor based on SAW device was fabricated

and applied in the analysis of urine and blood samples, with a detection range of 0.5-1.5 mg/dl [79, 80]. In another study [81], the developed bioelectronic tongue provided a simple and direct procedure to detect the concentration of urea in real samples without the necessity of eliminating the alkaline interferences or 14

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compensating endogenous ammonia. A urea biosensor was reported using photocurable polymeric membranes with ISFET as the transducer, which possessed a response time of 2 min with a detection range of 0.04-36.0 mM [82].

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For detection of phenolic compounds, a series of enzymatic biosensors by means

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of laccase [83], tyrosinase [84], peroxidase enzymes [85] have been developed as

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BioETs. These sensors employed the modified enzymes for special oxidization of the phenolic compounds into their quinones, which were directly measured through an

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amperometric sensor. Artificial Neural Networks (ANN), Linear Discrimination Analysis (LDA) and Principal Component Analysis (PCA) were used for data

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processing. This approach has already been applied toward the analysis of wines [86, 87] and beers [88, 89]. Xavier Cetó and co-workers has developed a BioET based on

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voltammetric enzyme-modified graphite-epoxy electrodes for the determination of three major phenolic compounds found in beer, namely ferulic, gallic and sinapic acid

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[89]. Fig. 4 presents the schematic diagram of voltammetric BioET method. More specifically, other applications including the analysis of polyphenols and resolution of their mixture have been also explored [90-92]. It has been demonstrated that phthalocyanines (MPc) and their sandwich type lanthanide derivatives (LnPc2) can

also been used as electron mediators in tyrosinate biosensors [93, 94].

Figure 4

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3.2 Gustatory receptor-based biosensor Although the electronic tongues can produce analytically useful information

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through the analysis of multi component matrices, there still exists a certain gap between the ET systems and biological taste, which mainly lies in the biological

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receptor structures and information coding mechanisms. In this case, the gustatory

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receptors-based biosensors exhibit their inherent advantages and could be utilized as other biorecognition alternative to taste sensing. Cells, tissues or receptors which can

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be immobilized with sensor surface as biometric sensing elements, can collect the functional information of bioactive analytes with high sensitivity and selectivity

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[95-97].

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The living taste receptor cells (TRCs) have been employed in the construction of

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mimic bioelectronic tongues for taste assessment. Chen and co-workers [98] cultured taste cells (type II cells and type III cells with different expressed taste receptors, as

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shown in Fig. 5(a)) on the LAPS for the purpose of specific sensation based on taste firing encoding. Fig. 5(b) shows a schematic graph of a LAPS detection system. Fig. 5(c) shows the statistics of firing rate with different stimuli. It was found that firing rate of taste cells is concentration-dependent of stimulus [Fig. 5(d)]. From PCA analysis of the temporal firing, it was demonstrated that response from different types of taste receptor cells could be discriminated [Fig. 5(e)]. Analogous work was carried out by Zhang et al. [99]. The combination of LAPS and TRCs was fulfilled to test the taste cell response to taste stimuli, namely NaCl, HCl, MgSO4, sucrose and glumate.

Similarly, a novel sweet taste cell-based biosensor for tastants detection was reported 16

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[100, 101]. The human colorectal carcinoma NCI-H716 cell lines, which express α-gustducin and T1R1/T1R3 as sweet taste receptors were cultured on the carbon screen-printed electrode. Poly-L-ornithine and lamimin coating was undertaken to

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improve adhesion in extracellular matrix. In order to investigate the cell-to-cell

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communication between type II (sour) and type III (sweet, bitter and umami) taste

cells, a serotonin sensitive sensor based on LAPS chip was fabricated [102]. The

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sensor performed with a detection limit of 3.3×10-13 M and a sensitivity of 19.1

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mV/decade. More interestingly, Wu et al. [103] successfully prepared ATP sensitive DNA aptamer on LAPS chip, to detect the local ATP secretion from single TRC

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responding to tastant mixture, thereby investigating the mechanism of taste signal

Figure 5

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transmission and processing.

For taste transduction, the response of taste receptor cells to tastants is firstly

coded in taste buds of the epithelium by action potentials. Thus if the taste buds are employed as sensitive materials in developing bioelectronic tongues, the bionic design will possess high performance in taste detection. Liu et al. employed microelectrode arrays (MEAs) to record electrophysiological activities of taste epithelium, building a platform to investigate detections and recognitions of basic tastes [104], as shown in Fig. 6(a). This combination offers several advantageous characteristics. Firstly, MEAs 17

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can record the extracellular electrophysiological activities of cultured excitable cells or tissues from recording sites in a long-term manner [105-107]. Moreover, the information of taste perception can be well preserved in an intact tissue and primary

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structure. Therefore, it is more convenient to realize in vitro detection of the neural

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potentials of taste receptor cells to taste stimuli. Furthermore, unlike cell networks

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cultured on MEAs which are limited to a two-dimensional circumstance and which may lose internal cell-to-cell communications through biochemical and mechanical

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cues, biological tissue such as taste epithelium can offer three-dimensional formation with inherent interaction between neighboring cells [108-110]. In their research, the

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electrophysiological signals of taste receptor cells to five basic taste stimuli were extracted. The recorded action potential displayed different spatiotemporal patterns

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for different taste and the temporal characteristics were derived by both time-domain and frequency-domain analysis [Fig. 6(b)]. On basic of this platform, Liu also

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investigated the extracellular potentials in the taste epithelium for bitter detection using 32-channel MEAs with the diameter of 30 μm. They found that stimulation of

different bitter substances such as quinine, denatonium and cycloheximide significantly evoked specific responses respectively, and with the increase of concentration of bitterness, firing rate, amplitudes and power spectrum, representing electrophysiological characteristics, also had a visible increase [111]. Successive and similar works had been carried out for salt sensing [112] and umami evaluation [113]. Additionally, for the purpose of sweeteners analysis, a 60-channel planar MEA device was employed and natural sugars (glucose and sucrose), artificial sweeteners 18

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(saccharin and cyclamate) and real samples (Coca-Cola) were chosen as testing samples[114]. In the recent decade, the advances in the research of taste transduction

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mechanism have made a significant impact on the development of biomimetic

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receptor-based biosensors for chemical sensing. In an interesting study, the membrane

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fractions of HEK-293 cell containing the successfully expressed T2R4, which is a human bitter receptor, were extracted and immobilized on the gold surface of QCM

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device [115]. This biosensor showed its dose-dependent response to denatonium, with

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high sensitivity (1.21 kHz mM-1) and high specificity.

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Figure 6

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3.3 Nanotechnology-based biosensor With significant advances in the nanotechnology, the combination of

nanomaterials and biological sensing elements to selectively recognize biological molecules has promoted the development of novel nanobiosensors. A great number of nanomaterials with different sizes, shapes, and unique properties, such as carbon nanotubes (CNT), grapheme, conducting polymer nanotube (CPNT) and silicon nanowires (SiNW), have been employed for biosensing because of their unique physical, chemical, mechanical, magnetic, and optical properties, and these nanomaterials have notably enhanced the sensitivity and specificity of detection. Most biological processes involve electrostatic interactions and charge transfer, which can 19

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be directly determined by nanomaterials-based electronic device. Consequently, these types of biosensor will be the most suitable for biological sensing. Nanotechnology has been combined with the enzymatic biosensor design. A

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multisensory system formed by nanostructured biosensor based on phenol oxidases

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has been constructed for the analysis of grapes [116]. In this work, enzymes were

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immobilized in a nanostructured lipidic layer with a structure similar to that of the biological membranes, and this biomimetic environment could help to preserve the

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functionality of the enzyme and improve the dynamic behavior and detection limit (in the range of 10-7-10-8 mol/L). Recently, several similar research works also focus on

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the nanostructured biomimetic biosensor for phenol sensing [93, 94, 117, 118]. Polyaniline nanofibres deposited on microelectrodes have shown to be efficient

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sensoactive layers in taste sensors for orange juices with different kind of orange ant degradations through variations of the presence of citric acid[119].

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In another study, an artificial taste sensor utilizing the human bitter taste receptor

protein was immobilized on a single-walled carbon nanotube field effect transistor (swCNT-FET) with lipid membrane, enabling a so-called “bioelectronic-super-taste (BST)”. The elaborated BST device could detect bitter tastants at 100 fM concentrations and distinguish between bitter and non-bitter with similar chemical structures

[120].

More

interestingly,

a

caboxylated

polypyrrole

nanotube

(CPNT)-based FET with human taste receptor protein, hTAS2R38 functionalization was developed as a nanobioelectronic tongue (nbe-tongue) which could display human-like performance with high sensitivity and selectivity [121]. Fig. 6(c) presents 20

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the schematic diagram of the sensor device. In their research, taster type (PAV) hTAS2R38 modified CPNT-FET could exclusively respond to target bitterness compounds, namely, phenylthiocarbamide (PTC) and propylthiouracil (PROP), with a

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high sensitivity at concentrations as low as 1 fM. On the contrary, no significant

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changes were observed in the nontaster type (AVI) hTAS2R38 modified ones in

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response to the target bitter tastants, as shown in Fig. 6(d). In addition, the fabricated nbe-tongue exhibited different bitterness perception to mimic the function of the

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human tongue through the test of real vegetable samples containing antithyroid toxin.

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4. Conclusion

There has been an extensive demand for (bio)chemical information acquiring in

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the different human life aspects, such as environmental monitoring, healthcare and

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food quality. Among the various standards evaluation, taste assessment leads an

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important role and has extensively aroused the social concerns. The emerging electronic tongue (ET) and bioelectronic tongue (BioET), which employ electrochemical sensors or biosensors array, provide a useful platform for fast, simple, clear gathering of taste information. Nowadays, the developed ET and BioET have exhibited well correlation with the human sensory panel and can effectively mimic the human taste sensors and their communication with the human brain. Through the combination with different chemometric processing, the sensors have showed intelligent capability for recognizing the qualitative and quantitative composition of multispecies solutions. Although all the achievements presented in this review seem to be very 21

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promising, these devices are still in an early stage of development, especially bioelectronic tongues. More effort should be made to further extending their applications in food industry and the other fields. Apart from this, the noteworthy

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limitation of drift in sensor signals, which may be caused by sensor aging and surface

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contamination, is still one of the weaknesses that should be solved. Consequently, the

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effective compensation models for specific correction of sensor response should be constructed and periodically undertaken. What is needed are optimized basic

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conditions on simplicity, reproducibility, accuracy, reliability for ET and BioET, which will eventually pave the way for their encouraging future. The value of their

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related research and development is seriously underestimated and needs to be reevaluated. In our opinion, there will still be an increase of research and commercial

te

d

interests in this area in the near future.

Ac ce p

5. Acknowledgement

This work was supported by International Cooperation Project between NSFC

and RFBR (No. 812111252), Marine Public Welfare Project of China (No. 201305010), Ministry of Education Doctoral Station Foundation of China (No. 20120101130011).

22

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extracellular potentials in the taste epithelium for bitter detection, Sensors and

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[112] Q. Liu, F. Zhang, D. Zhang, N. Hu, H. Wang, K. Jimmy Hsia, et al., Bioelectronic tongue of taste buds on microelectrode array for salt sensing,

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Biosensors and Bioelectronics, 40(2013) 115-20.

[113] D. Zhang, F. Zhang, Q. Zhang, Y. Lu, Q. Liu, P. Wang, Umami evaluation in

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taste epithelium on microelectrode array by extracellular electrophysiological

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recording, Biochemical and biophysical research communications, 438(2013) 334-9. [114] F. Zhang, Q. Zhang, D. Zhang, Y. Lu, Q. Liu, P. Wang, Biosensor analysis of natural and artificial sweeteners in intact taste epithelium, Biosensors and Bioelectronics, 54(2014) 385-92. [115] C. Wu, L. Du, L. Zou, L. Huang, P. Wang, A biomimetic bitter receptor-based biosensor with high efficiency immobilization and purification using self-assembled aptamers, Analyst, 138(2013) 5989-94. [116] C. Medina-Plaza, J. de Saja, M. Rodriguez-Mendez, Bioelectronic tongue based on lipidic nanostructured layers containing phenol oxidases and lutetium bisphthalocyanine for the analysis of grapes, Biosensors and Bioelectronics, 57(2014) 276-83. [117] I.M. Apetrei, C. Apetrei, Biosensor based on tyrosinase immobilized in single-walled carbon nanotubes modified glassy carbon electrode for epinephrine 34

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detection. [118] I. Apetrei, M. Rodriguez-Mendez, C. Apetrei, J. De Saja, Enzyme sensor based on carbon nanotubes/cobalt (II) phthalocyanine and tyrosinase used in pharmaceutical analysis, Sensors and Actuators B: Chemical, 177(2013) 138-44.

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[119] E.S. Medeiros, R. Gregório, R.A. Martinez, L.H. Mattoso, A taste sensor array

based on polyaniline nanofibers for orange juice quality assessment, Sensor Letters,

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7(2009) 24-30.

[120] T.H. Kim, H.S. Song, H.J. Jin, S.H. Lee, S. Namgung, U.-k. Kim, et al.,

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“Bioelectronic super-taster” device based on taste receptor-carbon nanotube hybrid structures, Lab on a Chip, 11(2011) 2262-7.

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[121] H.S. Song, O.S. Kwon, S.H. Lee, S.J. Park, U.-K. Kim, J. Jang, et al., Human taste receptor-functionalized field effect transistor as a human-like nanobioelectronic

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tongue, Nano letters, 13(2012) 172-8.

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Legends

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Figure 1. (a)The diagram of taste sensing system. (b) Radar chart as pattern recognition of foodstuff with different taste properties. (Reprinted with permission

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from ref. 13.)

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Figure 2. (a) Schematic image of the valinomycin-modified grapheme FET device. (b)

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The fabricated valinomycin-modified grapheme FET showed a sensitivity to K+, over the concentration range from 10nM to 1 mM. (c) The schematic section and physical

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top-view of InN-modified ISFET. (d) The InN-modified ISFET exhibited a sensitivity of 58.3 mV/pH and the current variation ratio was estimated to be 4.0%/pH.

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(Reprinted with permission from ref. 30 and ref. 31.) Figure 3. (a) Schematic representation for the fabricated thrombin aptamer

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functionalized SWNT-FET biosensor. (b) Real-time determination for the specific binding of thrombin molecules under increasing concentrations to thrombin aptamer functionalized SWNT-FET biosensor. (Reprinted with permission from ref. 66.) Figure 4. The schematic diagram of voltammetric BioET method. Signals extracted

from sensor array were firstly compressed by FFT and then input in the ANN to build multidetermination model. (Reprinted with permission from ref. 78.) Figure 5. (a) Different taste receptors were expressed in Type II and Type III cells for respective stimuli. Meanwhile, the neurotransmitter ATP was transmitted between two type cells. (b) The LAPS set-up for extracellular electrophysiological recordings of 36

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taste receptor cells. (c) The statistics of firing rate with different stimuli. (d) The pH-dependency of firing rate on sour stimuli. (e) PCA analysis of the temporal firing

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response to sour (blue) and ATP (red). (Reprinted with permission from ref. 89.) Figure 6. (a) The schematic diagram of the tissue biosensor, which had a combination

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of microelectrodes and taste epithelium to record the extracellular potentials of taste

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buds to taste stimuli. (b) The average amplitude and duration of signals in time domain to different basic taste stimulations. (c) The schematic diagram of a liquid-ion

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gate FET using hTAS2R38-functionalized CPNT. (d) Different bitterness perception of PAV-CPNT-FET and AVI-CPNT-FET for the target bitter tastants (PTC). The

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former showed a high sensitivity at concentrations as low as 1 fM while the latter

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exhibited no significant change. (Reprinted with permission from ref. 98 and ref. 111.)

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Table 1. Summary of electronic tongues including sensor type, sensing materials, data

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processing algorithm and applications

Table 2. Summary of bioelectronic tongues including biomolecule type, transducer part, biological recognition component and target molecules

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Data processing algorithm

Ref

ISEs, PVC-plasticized cation- and anion-senstive membranes, Chalcogenide glass

Bitterness evaluation of pharmaceuticals

PLS, 3wayPLS

[11]

ISEs, Chalcogenide glass, Plasticized polyvinylchloride membranes

Bitter taste in red wine, wine age prediction

PLS-DA, MLR, PCA

[7, 8]

Potentiometric sensors with PVC membranes and Chalcogenide glass

Taste and flavor of beer

PCA, CCA, PLS

[9,10]

Lipidic membranes with active substances such as trioctylmethylammonium chloride, oleic acid and gallic acid, etc.

Five basic taste evaluation, tea, milk, taste suppression in pharmaceuticals

PCA

[12-16,17, 20,22]

ISFET, photocurable polyurethane membranes

Mineral waters, grape juice, wine samples

HCA, PCA, PLS

[28,29]

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LAPS, PVC membranes with ionophores such as N,N’-tetrabutyldipicolinediamide, etc.

Heavy metals detection in seawater

Noble metal electrodes, platinum, gold, iridium, palladium, and rhodium

Tea, milk, juice, detergents

PCA, PLS, ANN

[35,38-40]

Noble metal electrodes, platinum, gold, palladium, titanium, nickel, etc.

Chinese distilled spirit, Longjing tea

MVDA, PCA

[44]

Platinum plates, carbon paste electrodes, polypyrrole, phthalocyanines, etc.

Oleuropein, ligstroside, alcohol in beers

PCA, PLS

[46,50]

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Impedance

Optics

Mass

[32]

Graphite-epoxy electrodes

Wines

PCA, ANN

[48]

Gold disks, carbon paste electrodes, Phthalocyanines, polypyrrole and perylenes

Red wines

PCA

[47]

platinum disks with electrodeposition layers (3-methylthiophene, aniline and pyrrole)

Five taste properties discrimination

PCA

[51]

Carbon paste electrodes modified with metallic phthalocyanines and polypyrrole-based electrodes

antioxidants analysis present in foods

PCA, PLS

[55]

Polypyrrole

Water and taste substances

PCA

[59]

Polylactic acid, carbon black, polyvinyl alcohol, etc.

Standard taste solutions

PCA

[60,61]

Urethane-acrylate, 2-cyanophenyl

Anionic surfactants

Dye/silicon and dye/lipid/ PVC-PVAc-PVA

Basic taste solutions

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Voltammetry

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Applications

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Potentiometry

Sensor type & Sensing materials

QCM, dioctadecyldimethylammonium poly (styrene sulfonate) Dual shear horizontal SAW

[62] PCA

Bitterness intensity and 39 astringency of beer Basic tastes analysis

[63] [66-68]

PCA

[69]

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Table 2 Summary of bioelectronic tongues including biomolecule type, transducer part, biological recognition component and target molecules

Cell

Target molecules or substances

Ref

Platinum disc, epoxy-graphine

Glucose oxidase

Glucose

[74]

SWNT-FET

Aptamer

Thrombin

[75]

FET

Creatininase, creatinase and urease

Creatinine and urea

[76]

FET

Glutamate oxidase

Glutamate

[77]

SAW

Urease

Urea

[79,80]

ISFET

Urease

Urea

[82]

Gold nanoparticles-modified glassy electrodes

Tyrosinase

polyphenols

[84]

Graphite-epoxy voltammetric electrodes

Tyrosinase, laccase, Copper nanoparticles

ferulic, gallic and sinapic acid

[89]

LAPS

taste receptor cells

Taste substaces

[98,99]

NCI-H716 cell lines

Sweet tastants

[100]

taste receptor cells

serotonin

[102]

taste epithelium

Bitter substances

[111]

taste epithelium

Salt substances

[112]

taste epithelium

Umami substances

[113]

taste epithelium

Sweeteners

[114]

QCM

membrane fractions of HEK-293 cell containing bitter receptor

Denatonium

[115]

LAPS

ATP-sensitive DNA aptamer

ATP secretion

[103]

swCNT-FET

Human bitter taste receptor protein hTAS2R38

PTC and PROP (bitter substances)

[120]

CPNT-FET

Taster type (PAV) and non taster type(AVI) hTAS2R38

PTC and PROP (bitter substances)

[121]

Carbon screen-printed electrode LAPS MEAs MEAs

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Tissue

MEAs

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MEAs

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Biological recognition component

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Enzyme

Transducer part

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Biomolecule type

Receptor

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Biographies Da Ha received his B.S. and Ph.D. degree of biomedical engineering in Zhejiang

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University, P.R. China in 2009 and 2014. His research interests include biomedical sensors and chemical sensors.

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Ning Hu received his B.S. and Ph.D. degree of biomedical engineering in Zhejiang

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University, P.R. China in 2009 and 2014. Now he is a postdoctor of biomedical engineering of Zhejiang University. His work includes cell-based biosensor, biosensor

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instrument establishing and signal processing.

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Qiyong Sun received his BS degree in Shandong University, P. R. China in 2012. Presently, he started his Ph.D. thesis in the Department of Biomedical Engineering of

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chemical sensors.

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Zhejiang University, from 2012. His research interests include biomedical sensors and

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Kaiqi Su received his B.S. and M.S. degree of biomedical engineering in Zhejiang University, P.R. China in 2011 and 2014. Now he is a Ph.D. candidate of biomedical engineering of Zhejiang University. His work includes biosensor instrument establishing, software design and signal processing. Hao Wan received his BS degree in Huazhong University of Science and Technology,

P. R. China in 2010. Presently, he started his Ph.D thesis in the Department of Biomedical Engineering of Zhejiang University from 2010. His research interests include biomedical sensors and chemical sensors. Haibo Li received his BS degree in Tianjin University, P. R. China in 2012. Presently,

he started his MS thesis in the Department of Biomedical Engineering of Zhejiang 42

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University, from 2012. His research interests include chemical sensors. Ning Xu received her BS degree in Zhejiang University, PR China in 2012. Presently, she started her MS thesis in the Department of Biomedical Engineering of Zhejiang

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University from 2012. Her research interests include chemical sensors.

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Fei Sun received his BS degree in Tianjin University, P. R. China in 2013. Presently,

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he started his MS thesis in the Department of Biomedical Engineering of Zhejiang University, from 2013. His research interests include chemical sensors.

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Ping Wang received his BS degree, MS degree and Ph.D. degree in electrical engineering from Harbin Institute of Technology, Harbin, P. R. China in 1984, 1987

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and 1992, respectively. He is currently a professor of Biosensors National Special Lab, Department of Biomedical Engineering of Zhejiang University. He is also a visiting

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professor in Electronic Design Center of Case Western Reserve University, USA and a visiting scholar in Department of Biological and Agricultural Engineering of

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University of Arkansas, USA. His research interests include biomedical sensors, chemical sensors and measurement technique.

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