Design of smart chemical ‘tongue’ sensor arrays for pattern-recognition-based biochemical sensing applications

Journal Pre-proof Design of smart chemical 'tongue' sensor arrays for pattern-recognition-based biochemical sensing applications Zi-Han Chen, Qian-Xi Fan, Xin-Yue Han, Guoyue Shi, Min Zhang PII:

S0165-9936(19)30532-1

DOI:

https://doi.org/10.1016/j.trac.2019.115794

Reference:

TRAC 115794

To appear in:

Trends in Analytical Chemistry

Received Date: 15 September 2019 Revised Date:

19 December 2019

Accepted Date: 21 December 2019

Please cite this article as: Z.-H. Chen, Q.-X. Fan, X.-Y. Han, G. Shi, M. Zhang, Design of smart chemical 'tongue' sensor arrays for pattern-recognition-based biochemical sensing applications, Trends in Analytical Chemistry, https://doi.org/10.1016/j.trac.2019.115794. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. 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. © 2019 Published by Elsevier B.V.

Design

of

smart

chemical

'tongue'

sensor

arrays

for

pattern-recognition-based biochemical sensing applications Zi-Han Chen1,2, Qian-Xi Fan1, Xin-Yue Han1, Guoyue Shi1, Min Zhang1* 1

School of Chemistry and Molecular Engineering, Shanghai Key Laboratory for Urban Ecological Processes and Eco-Restoration, East China Normal University, 500 Dongchuan Road, Shanghai 200241, China.

2

Department of Chemistry, Shanghai Key Laboratory of Molecular Engineering of Polymers and iChEM, Fudan University, Shanghai 200433, China.

Corresponding Author E-mail address:(*) [email protected]

Abstract Conventional molecular recognition was tightly related to the development of analyte-specific sensor. However, all most every biochemical process are not decided on only one factor. When several factors were imported simultaneously, the established sensor could be seriously interfered and gave the wrong response. In this regard, chemical tongue-mimic sensor array was promoted to recognize a set of analytes, which concerned each component of mixtures. This review, focused on the development of chemical “tongue” sensor arrays from recent years, and gave enlightening examples about how to design integrated sensor system, how to choose the responsive signals and explain the mechanism of each used. As for applications, this review concluded the status of what chemical or biochemical species could be discriminated, what the advantages or drawbacks they had and the novel mechanism they used. In the last, this review also pointed out the limitations and future of related field.

Keywords: tongue-mimic; chemical sensor array, pattern recognition, multiple analysis, molecular recognition

1. Introduction The trends in development of the chemical/biological sensors are selective ones and cross-response ones. The current highly selective of chemical or biochemical sensors based on the specific molecular recognition, especially “lock and key” principle, in which a target-specific recognition unit and a signal transduction component are always needed [1-5]. Such ideal approaches include aptamers (single-stranded DNA/RNA binding with biomolecules) [6], antibodies (antigen-antibody reaction) [7], enzymes (precise bio-catalysis) [8], other various bioconjugation interactions (e.g. streptavidin/biotin) [9-10] or even some non-specific conjugates [11]. In general, many physiological processes or metabolism are linked with multiple biochemical species and only a single sensor could not always achieve [12]. For example, oxidative stress is usually derived from reactive oxygen/nitrogen species (ROS, RNS), which involves superoxide radical (·O2-), hydroxyl radical (·OH), peroxynitrite (ONOO-) and so on [13-14]. So precise determination of biochemical compositions is vital to disease theranostics with complicated pathogenesis [15]. To date, simultaneously monitoring multiple analytes has been greatly investigated through methodology including design of the dual-responsive probe, concept of the logic gate. [16-18]. The most efficient way is to set up multiplexed sensors toward multiple analytes or give a series of signal outputs to decrease false-positive rate. However, it seems to need more massive and tedious work to access target-specific sensors by trial and error, because the design of selective method always needs a “lock and key” principle and such specific mechanism should be set up in view of practical uses [19]. Diminishing and overcoming the effects from interfering species are the chief problems of analytical chemistry. When a sensor meets a group of analytes with similar structures or physical and chemical properties, the reliability of this strategy is often doubtful. Starting from this angle, the novel and smart chemical tongue-mimic sensor array is promoted toward this key point [1, 20-22]. In this issue, several sensors are combined in an array format, which is very similar to human sensory system (e.g. tongue) that can accept external stimuli from environment [22-24]. Then such responses of tongue are collected and transferred in chemical or electrical signals to cerebral cortex, where it will tell body what it tastes (Figure 1). The same principle as chemical tongue-mimic sensor array, signals from different recognition components come together and are handled by data mining process (e.g. principal component analysis, PCA), and then it will give the results of what it senses or what it contains [25-26]. Therefore, based on the abundant database and protocol programming, the different species can be directly exhibited in 2D or 3D graphs, which reflect their different level of separation. In recent years, array-based chemical “tongue” has been more developed based on optical signals, and their applications are focused on chemical sensing [27], diagnostics [28] and drug discovery [29], but they lacked novel design from signals and creative application environment. This review will introduce how to design chemical sensor arrays and illustrate several classical examples, what chemical or biological species can be detected or classified, their meanings with human healthcare and the possible problems or outlooks in the future.

Figure 1 Illustration of the mechanism of chemical “tongue” sensor array: The sensor array is an integrated mode from several basic sensor elements, and each sensor could give abundant responses to multi analytes like the receptor cells in human tongue. Then, diverse responsive signals are collected and processed entirely to access a final fingerprint map, which reflects the results of each analyte.

2. Design of Chemical “Tongue” Sensor Array The concept of chemical “tongue” is the development and extension of electronic nose [30] and electronic tongue [31]. Early in 1982, the first important example of artificial electronic sensor array was learned from the mammalian olfactory system [32]. Dodd and Persaud creatively used 3 commercially available gas detectors made from copper-doped tin oxide semiconductors to detect odorants [32]. As they described, the function of transducers was more likely to primary neurons. Although there were very small differences among detectors, the data processing like secondary neurons could amplifier the discrepancy signals through pattern recognition mechanism, and finally discriminated the diverse odors. Therefore, the design or choose recognition elements was focal to develop chemical “tongue”. From recent literatures, the most popular ones were mainly from organic molecules, nanoparticles and other lanthanide-based complexes. No matter target-specific sensors or chemical “tongue” sensor array, it is fundamental to following certain sensing/transduction mechanisms for recognition elements. 2.1 Organic molecules Structural features and functional groups are meaningful to the organic molecules design and synthesis. In this respect, chemical sensor arrays based on organic reactions and interactions are the chief choices. As for the signals, optical properties are very simple and convenient to readouts within the field of organic chemistry (Figure 2A), so that any structural changes can partly induce the fluorescence or visible absorbance changes [33]. Organic dyes, as the most classical probes for sensing and imaging, are very suitable and available for designing of sensor arrays [34-36]. Porphyrins, coumarin and other aromatic compounds often exhibit diverse photoluminescence or colors, and they are very sensitive toward many metal ions (Figure 2B and 2C) [37-43]. There are several choices for design of organic-based sensor arrays. One way is to set up basic elements with different colors, so that the responsive optical signals or information could be transferred to digital signals through extracting and storing red-green-blue (RGB) values [36, 43-47]. Such data processing could greatly improve the accuracy of detection method and efficiently reduce the

effects from naked eyes. Another choice is based on the fluorescence spectrometer and it directly records the fluorescence intensity of each sample under photoexcitation. But this approach usually costs too much time or efforts and relies on abundant parallel tests.

Figure 2 Design of chemical “tongue” sensor arrays based on organic molecules or polymers. (A) 8-Hydroxyquinoline (8-HQ) based sensors and the extended conjugated chromophore (blue) [42]. Copyright 2008 American Chemical Society. (B) Structures of thiocoumarins and coumarin used in a sensor array [38]. Copyright 2019 The Royal Society of Chemistry. (C) Chemical structures of diol-selective benzyl viologens (BV) to discriminate syrups and honeys [39]. Copyright 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim. (D) Chemical structures of polyethylene glycol-block-PLL-based (PEG-b-PLL) polymers and the cross-reactive interactions toward proteins [48]. Copyright 2019 American Chemical Society. (E) Structures of cationic fluorescent polymers with multiple types of recognition elements and fluorophores [49]. Copyright 2019 American Chemical Society. Supermolecules, macromolecules and polymers are a specific series in the field of organic chemistry. They often have large molecular structure and formula, and different molecular units decide various functions of each. Therefore, in this format, the design of novel chemical sensor arrays is tightly with the sensing unit structure in polymers [48-49]. A polymer-based sensor mainly contains two functional parts, recognition fragment and responsive part. Much interaction or reaction mechanisms have been embodied including electrostatic interactions, hydrophobic interaction, hydrogen-bond, cross-reactivity and enzyme catalysis, which could be regulated by pH, ionic strength and take place toward both specific and non-specific analytes (Figure 2D and 2E) [50-52]. Meanwhile, these designs are more available in discrimination of macromolecules like proteins and amino acids [53]. 2.2 Nanomaterials

Nanomaterials with optical properties are very popular to construct chemical “tongue” sensor arrays. Obviously, the surface chemistry is the essential issue when considering the proposed mechanism [54]. Because nanomaterials have merits including smaller sizes, high surface-to-volume ratio, unique physical or quantum properties and functionalized surface, it is very convenient to interact or modify ligands to form a response-recognition conjugation, and this format is common in biochemical sensing [55-57]. Great examples contain gold nanoparticles (AuNPs) with unique absorbance (Figure 3A), quantum dots (QDs) [58-60] and gold nanoclusters (AuNCs) with fluorescence [61-65], and lanthanide-based nanomaterials [66-70]. It is revealed that metal-ligand interactions, Forster resonance energy transfer (FRET) and plasmon-induced fluorescence quenching are prevailing in the accordance with sensing mechanisms (Figure 3C) [59, 71]. A typical case should be focused on the Qu’s work (Figure 3B). In their report, 7 kinds of fluorescent nanoparticles (AuNCs and QDs) combined with graphene oxide (GO) were designed as the chemical sensor array, which would initially result in fluorescent off due to the strong quenching effect of GO [72]. When proteins were added, each protein with different electricity and structure would induce different interactions toward GO, and fluorescent nanoparticles would recover to some extent. As for AuNPs, many literatures were devoted in biomolecules-functionalized AuNPs to design of novel sensor arrays, where the aggregation and disaggregation of AuNPs could cause obvious absorbance changes [73-77]. Single-strand DNA (ssDNA) with negative charge and multiple recognition sites was the best choice to form the sensor units and stabilized the AuNPs in aqueous solution [59, 76, 78]. Sometimes, the same nanomaterials with different fluorescent properties regulated by synthetic conditions were also in consideration.

Figure 3 Design of chemical “tongue” sensor arrays based on several nanomaterials. (A) FAM-labeled ssDNA functionalized AuNPs [59]. (FAM: 5-Carboxyfluorescein; ssDNA: single strand DNA; AuNPs: gold nanoparticles). Copyright 2015 American Chemical Society. (B) AuNCs, CDs, QDs, AgNCs, GQDs fabricated novel sensor array in nanoscale [72]. (AuNCs: gold nanoclusters; CDs: carbon dots; QDs: quantum dots; AgNCs: silver nanoclusters; GQDs: graphene quantum dots). Copyright 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim. (C) FRET-based BPB-QDs conjugates for discrimination of proteins [71]. (BPB: bromophenol blue;

SA-QD: streptavidin conjugated quantum dots). Copyright 2016 American Chemical Society. 2.3 Others Besides organic molecules and nanomaterials, much attention has also been concentrated on organic-inorganic hybrid sensor array in another format [79-80]. Recently, our group developed several metal-organic ligand complexes based on lanthanide element (Tb3+, Eu3+). It was early reported that biomolecules including proteins and ssDNA could strongly bind to trivalent lanthanide ions, which would exhibit luminescence of Tb3+, Eu3+ Ce3+ or Dy3+ through an intramolecular energy transfer called antenna effect [81-82], and ssDNA also provided excellent binding cites for the coordination with other metal ions [83-84]. Among them, Tb3+, with large stokes shift spectral properties has been revealed that G/T-rich sequenced ssDNA could greatly enhance the emission intensity up to two thousand times from previous report [82]. Therefore, the luminescence intensity of Tb3+ could be regulated by ssDNA sequences. We examined [G3T]n (n = 3~10) sequences to screen better effective sensitizing ligands toward Tb3+, and [G3T]3, [G3T]5 and [G3T]6 were finally chosen to construct a novel sensor array due to their strongest intensity of Tb-[G3T]n complex (Figure 4A) [66]. In another report, A/C/G/T-rich ssDNA oligomers with different bp (4~24) were firstly screened to sensitize Eu3+, then Eu/C16 and Eu/T16 were applied to discriminate of 17 metal ions (Figure 4B) [67]. We also realized Tb3+-BSA (bovine serum albumin) conjugates and Tb-guanosine/deoxy-guanosine monophosphate (Tb-GMP/dGMP) coordination polymers to response various metal ions (Figure 4C and 4D) [69, 70]. The above examples were based on the structure or conformation of lanthanide complexes due to antenna effect as we described above, in which metal ions competed with lanthanide ions by grabbing ligands and induced the changes of the luminescence intensity. And it was proved with the circular dichroism (CD) spectra and isothermal titration calorimetry (ITC).

Figure 4 Design of chemical “tongue” sensor arrays based on lanthanide nanomaterials. (A) Tb3+-[G3T]n sensor array for detection of 49 metal ions [66]. Copyright 2018 American Chemical

Society. (B) Sprouting unique sequence of ssDNA toward Eu and time-resolved luminescent assays for metals and biothiols [67]. Copyright 2018 American Chemical Society. (C) Tb3+-BSA regulated by pH to discriminate metal ions [70. (BSA: bovine serum albumin). Copyright 2019 American Chemical Society. (D) Tb-GMP/dGMP sensor array for sequentially pattern recognition of metal ions and biothiols [69]. (GMP: guanosine monophosphate; dGMP: deoxy guanosine monophosphate). Copyright 2019 Elsevier B.V. Inorganic nanoparticles coupled with organic molecules were also promoted by our group to the development of novel sensor arrays. The design strategies lie in the combination of their coordination interactions and spectral changes. Upconversion nanoparticles (UCNPs) usually exhibited fluorescence in the visible region, and it was natural for people to draft strategies with dyes related to biosensing. Our previous work has unveiled a dual-mode optical nanokit toward phosphate compounds based on Cu-UCNPs/TPPS (TPPS, a kind of commercial porphyrin compound) [85, 86]. The upconversion fluorescence spectra of UCNPs was largely overlapped with the absorption spectra of TPPS, which caused the upconversion fluorescence resonance energy transfer. However, the pH could effectively regulate the dual-mode signals, and such sensor array comprised of Cu-UCNPs/TPPS in different pH buffer (4, 4.5, 5). Oxidation-reduction reaction was also under our consideration. Polydopamine (PDA) derived from dopamine monomer was an ideal quencher for many inorganic fluorescent species (such as manganese(II)-doped zinc/germanium oxide nanoparticles) and from blocking of polymerization by redox mechanism, a novel inorganic-organic hybrid sensor array in a fluorescence “turn-on” format has been established toward the pattern recognition of many biothiols [87].

3. Applications of Chemical “Tongue” Sensor Array 3.1 Metal ions Metal ions are essential to every living organism. Too much or too little level of metal ions are deadly to everything. Conventional assays including inductively coupled plasma atomic emission spectrometer (ICP-AES), atomic absorption spectrometry (AAS) and inductively coupled plasma mass spectrometry (ICP-MS), focused on the properties of atoms like element mass or atomic spectrum [88-90]. However, these equipment with high accuracy is limited to professionals, high price and not portable enough. Therefore, easy-to-operate and identification of metal ions are the key problems to the future field of environment and healthcare. As for novel chemical “tongue” sensor arrays, most of the sensing mechanism is based on the coordination interactions. Typical examples of basic sensing elements involved biomolecules, dyes and nanomaterials. Tan and coworkers designed a dual channel multidimensional sensor consisted of FAM-labeled DNA and AuNPs [60]. Both DNA and AuNPs have negative charges and coulombic repulsive forces impeded them combined with each other. As we described in Section 1, recognition unit and transduction component are always needed in a sensor. In this work, the mechanism focused on the metal ions with different positive charges induced interactions between two negative species, and the fluorescent intensity of FAM and the absorption spectra of AuNPs were used to construct dual channel signals. 15 bp FAM-labeled A/C/T-rich ssDNA oligomers with dual

channel composed of 6 sensor elements. When 9 heavy metal ions were added, data including obvious fluorescence quenching and varying degrees of AuNPs aggregation were collected and analyzed by linear discriminant analysis (LDA) and principal component analysis (PCA). 9 metal ions with the same concentrations (500 nM, 100 nM and 50 nM) and the mixture of Cu2+ and Hg2+ with different concentration ratios could be successfully discriminated. Heavy metal, especially transition and noble element ions are common targets in such design, because these analytes are often attached to toxicity with stronger interactions toward molecules, which are tightly related to environment pollution and healthcare monitoring [91]. But according to the urgent need of food chain cycle and biochemical process, more and more metal ions should be under consideration. To solve this problem, metal ions are divided into groups with similar ionic structure or chemical properties to be analyzed. In 2002, Kool’s group developed a new class of DNA-like chemosensors called oligodeoxyfluorosides (ODFs) to sense metal ions [92]. This series of advanced molecules built on the phosphate backbone and exhibited excellent programmable synthesis by fluorescence monomers. However, most of the heavy metal ions could yield strong quenching effect. Therefore, to achieve better recognition of metal ions, their previous work has investigated various sequences within DNA-like oligomers, which provide diverse responsive signals for pattern-based recognition [93-97]. A set of 9 tetramers on PEG-polystyrene beads were used to totally discriminate 50 metal ions [98]. This pioneering trial divided them into 4 groups including alkali metals, alkaline earth metals, post-transition metals and lanthanides, which referred to the arrangement of periodic table of elements. Also, each group with different response range validated the coordination differences of each element. Our recent contribution also demonstrated the similar discriminated ability of 49 metal ions by using as few as three lanthanide-based time-resolved fluorescent sensors (Section 2.3) [66]. Although the above examples have revealed great potential in classifying multiple analytes, the sensing sensitivity of the above examples had little difference with traditional analyte-specific sensor and we think it was possible due to the affinity constant of metal ions and sensors. Not all the metals could be easily distinguished, lanthanides with the similar charge and sizes, suffered from difficulties in selectivity and low sensitivity [99]. To address this problem from the angle of complexes, Liu’s group devoted much efforts on rational ligand structures [100]. In their work, DNAzymes specific for lanthanides were screened in vitro selection and designed in a beacon model. The five trivalent lanthanide ions (Ln3+)-dependent DNAzymes offered distinction of 14 nonradioactive lanthanides referred to their minute differences. Through the typical examples of the applications above, we found that chemical “tongue” sensor array toward metal ions was tightly related to the metal coordination ability. The coordination between metal ions and sensor elements were usually depended on sizes and charges of metal ions. Therefore, it seems quite easy for recognition of metal ions by design of coordinated-response in a novel chemical “tongue” sensor array (Table 1). Table 1 Representative examples on the discrimination of metal ions using chemical “tongue”. Sensors

CdTe

QDs,

Numbe r of Sensors

Signals

Mechanism

Number of Targets

Ref.

6

Fluorescence

Metal-surface

7: Ag+, Hg2+, Pb2+,

[102

AgNCs, AuNCs FAM-labeled DNA 3 functionalized AuNPs

ligand coordination Metal-ssDNA coordination

Cu2+, Cr3+, Mn2+, Cd2+

]

9: Cd2+, Cr3+, Cu2+, Pb2+, Zn2+, Hg2+, Ag+, Mn2+, Sn4+

[60]

Metal-dyes coordination

11: Ag+, Ba2+, Ca2+, Cu2+, Fe2+, Fe3+, Li+, Mg2+, Mn2+, Ni2+, Zn2+

[103 ]

Metal-surface ligand coordination Metalquinolinolate coordination Host-metal and host-guest-meta l interactions

9: Ni2+, Co2+, Mn2+, Cu2+, Ca2+, Ag+, Cd2+, Fe2+, Fe3+ 10: Ca2+, Mg2+, Cd2+, Hg2+, Co2+, Zn2+, Cu2+, Ni2+, Al3+, Ga3+ 16: Ca2+, Mg2+, Cd2+, Hg2+, Co2+, Zn2+, Cu2+, Ni2+, Fe3+, Mn2+, Pb2+, La3+, Ce3+, Er3+, Th4+, UO22+ 49: alkali-metal, alkaline-earth metal, transition/post-transitio n metal, lanthanide ions 17: alkali-metal, alkaline-earth metal, transition/post-transitio n metal 18: alkali-metal, alkaline-earth metal, transition/post-transitio n metal 14: Lanthanide ions

[104 ]

4

Dual-channel : Absorbance, Fluorescence Fluorescence

6

Fluorescence

6

Fluorescence

3

Fluorescence

Tb-[G3T]n conjugates

3

Fluorescence

Metal-ssDNA coordination

Eu/ssDNA probes (C16/T16)

2

Fluorescence

Metal-ssDNA coordination

Polydopamine-PEI

3

Fluorescence

Metal-surface ligand coordination

Curcumin-based sensors

3

Fluorescence

ODF sensors

6~9

Fluorescence

Metalfluorescent dyes coordination Metalfluorescent dyes coordination

Thioflavin T, Thiazole orange, Pyronine Y, N-methyl mesoporphyrin IX-doped Eu/GMP Gln/Arg/TG/MPA capped Mn-ZnS QDs 8-hydroxyquinolin e (8-HQ)-based sensors Host-guest complexes

57: alkali-metal, alkaline-earth metal, transition/post-transitio n metal, lanthanide

[42]

[105 ]

[66]

[67]

[106 ]

[99]

[98]

Functionalized ionic microgels

4

Absorbance

Metal-microgel s interactions

ions 10: Ba2+, Cr3+, Al3+, Mn2+, Pb2+, Fe3+, Co2+, Zn2+, Ni2+, Cu2+

[107 ]

Abbreviations: TG: alpha-thioglycerol; MPA: 3-mercaptopropionic acid; PEI: poly(ethylene imine) 3.2 Amino acids and Proteins As the basic functional components in all creatures, amino acids participate in almost biochemical process, and the side chain of which decided what roles it played in a reaction. Therefore, recognition of amino acids is correlated to the properties of side chain including positive or negative charges and aromaticity or hydrophobicity groups, and to achieve discrimination of multiple targets, specific molecular design should be under concerned. A group of novel chemical sensor arrays was constructed on supramolecular receptors and chemosensors. Cucurbit[n]-uril receptors (CB[n]) provided recognition sites for protonated amines in amino acids and hydrogen boding sites form C=O moieties [108]. Because the C=O moieties of the probes and carboxy oxygen in amino acids could produce electrostatic repulsion between each other, the receptor was much more sensitive to amino groups and amino-rich molecules. This approach could compare and predict the unknown samples by confirmation of how many amino or carboxy it had. Another effective strategy is a novel aggregation induced emission (AIE)-doped poly ionic liquid (PIL) photonic sphere with two channel optical properties [109]. The proposed sphere sensing platform used PIL units to induce unique intermolecular interaction toward diverse analytes, so a single sphere-based array could produce complicated and abundant responsive signals based on noncovalent interactions. Such recognition process could be learned and customizable toward more targets using the similar mechanism. By changing acquisition signals, Yu and coworkers developed a chemiluminescence sensing array based on luminol-functionalized silver nanoparticles. Because chemiluminescence is quite a slower process due to the generation of ·OH, time of luminescent signal to appear, time of reaching maximum luminescence and luminescent intensity were chosen to gain responses [110]. As revealed in Table 2, recognition of amino acids was quite easy because several strategies could be utilized and integrated. Table 2 Representative examples on the discrimination of amino acids or proteins using chemical “tongue”. Sensors

Number of Sensors

Signals

Number of Targets

Ref.

Luminol- AgNPs

3

7 amino acids: Cys, Pro, Phe, Arg, Thr, Glu, Tyr

[110]

cucurbit[n]-uril receptors (CB[n]) AIE-doped poly(ionic liquid) photonic spheres Aptamer-AuNPs

2

Ta, Tp, Chemilumines cence Fluorescence

10 basic amino acids

[108]

3

Fluorescence, Peak shift

20 natural amino acids

[109]

3

Absorbance

7 proteins

[58]

FAM-labeled DNA-AuNPs Nanomaterials-GO QDs-BPB Ionic Liquid−QDs Functionalized AuNCs Metal NPs-QDs DNA-NGO AgNPs DNA-AuNPs Metal nanomaterials

3

Absorbance

10 proteins

[59]

7 3 5 6

Fluorescence Fluorescence Fluorescence Fluorescence

10 proteins 10 proteins 8 proteins 10 proteins

[72] [71] [112] [62]

3 5 3 3 6

Fluorescence Fluorescence Absorbance Absorbance Chemilumines cence

8 proteins 9 proteins 10 proteins 11 proteins 12 proteins

[114] [113] [115] [60] [116]

Abbreviations: AgNPs: silver nanoparticles; Ta: time required for the signal to appear; Tp: time required to reach maximum luminescence; CB: cucurbit; GO: graphene oxide; NGO: Nanographene oxide Proteins, with the complex structure and complicated functions, are quite difficult to be identified precisely, and there are no analyte-specific interactions for proteins in an array format. When nanomaterials (AuNPs, QDs) were chosen to fabricate basic sensing units, the interfaces of sensors and targets were vital to solve this problem [58-60, 71-72, 111-112]. A simple and easy-to-operate method was constructed based on DNA-functionalized AuNPs. Aptamer-protected AuNPs could be stabilized in high level of salt, however, proteins with various molecular weight, isoelectric point and metal/nonmetal component, had great effect on the aggregation of AuNPs by taking over aptamer or absorption on AuNPs, which gave the discrimination of several proteins with huge differences [58]. Another interface-mediated way was derived from the catalytic activity of AuNPs due to the existence of Au3+ on the surface of AuNPs. In Wei’s work, 4-nitrophenol (yellow) reacted with NaBH4 to generate colorless 4-aminophenol under the exposure of AuNPs and a novel color-change time was chosen as readout according to the absorbance changes [74]. With the help of the catalytic process, the detection of limitation for proteins could be lower to nanomolar than other similar work. Although these approaches could certainly discriminate proteins including BSA, HAS and HRP, biological species was quite more complex that any interfering species could easily change the status of AuNPs. Therefore, development of chemical “tongue” sensor array based on noble nanoparticles for real sample applications is still an urgent need. Another strategy from recent years was similar with the design of molecular beacon. Displacement of readout signals on the materials’ interfaces was common in discrimination of proteins. Pei’s work has systematically investigated the interactions and binding sites between dye-labeled DNA probes and nanoscale graphene oxide (NGO) [113]. Because most of the proteins have stronger affinity toward NGO, dye-labeled DNA probes were displaced and released to give a fluorescence “turn-on” signal. They also found such DNA-NGO could detect cells and microorganisms, which exhibited powerful sensing range and provided a versatile and optional platform. Fluorescent quantum dots or nanoclusters were also the good choices for discrimination of proteins, which contained amino acid-functionalized AuNCs [62,65], dual ligand functionalized AuNCs [63], nanoparticle-QDs complex [114] and gold nanodots [117]. Due to the mechanism of

fluorescence on the nanomaterials’ surfaces, these “turn off” strategies also have drawbacks when complicated samples were tested, and the current contributions could only recognize one or two components at one time. 3.3 Biothiols Biothiols are a significant set of biomolecules to maintain the physiological states in vivo, and they are the “guardians” of cells and organisms to clear the oxygen/nitrogen free radicals produced from oxidative stress reaction [118]. The most remarkable characteristic of biothiols is that they have a free thiol group (-SH) in the molecular structure, which usually has stronger chemical activity [119]. -SH is easily oxidized to disulfide bond (-S-S-) and loses its reactivity of reductant. Recent years, there have been many reports on detection of biothiols, especially cysteine (Cys), homocysteine (Hcys) and glutathione (GSH), and most of the approaches are based on the design of organic fluorescent probes in view of the reaction characteristics of -SH [120]. However, because different biothiols participated in various biochemical process, how to discriminate biothiols is still a difficult problem. To achieve this goal, there are two ways to be concerned. The first path was utilized the coordination of metal ions and -SH. As we described before, this kind of conventional interactions could be used for recognition of metal ions, but it could also be realized the discrimination of biothiols based on sensor-metal conjugates. Fluorescent carbon dots (CDs) [121], multicolor functionalized quantum dots (QDs) [122], fluorescent polydopamine (PDA) [123] and lanthanide complexes [64, 69] were successfully established to act as chemical “tongue” sensor arrays and could recognize more than three species with a -SH in the structure. Cu2+, Ag+, Hg2+ and Cr3+ were the most popular ones to interact with biothiols. This method is also limited by the affinity constant of metal ions. Another intriguing way was developed by our group [87]. The formation of PDA processed the steps of oxidation, cyclization, rearrangement and polymerization. Our previous work has revealed that reductants including biothiols and ascorbic acid could induce the inhibition of PDA synthesis, which provided an ideal way to discriminate Cys, Hcys and GSH based on the different chemical activities [125]. We also established a theory model about standard reduction potentials to reflect their diverse ability, which proved it was related to their reduced reactivity. The above examples have greatly concluded the progress of detection of biothiols in a novel stage, and more functional biomolecules with similar structures or chemical activities could be concerned. Table 3 Representative examples on the discrimination of biothiols using chemical “tongue”. Sensors

Number of Sensors

Signals

Number of Targets

Ref.

DA-Mn@ZGNPs CDs-Metal ions

3 5

Fluorescence Fluorescence

[87] [121]

Coated AuNPs Eu-ssDNA-Ag/Cu

3 4

Absorbance Fluorescence

PDA/PEIn–Cu2+

3

Fluorescence

CdTe QDs, CDs,

4

Ratiometric

3: Cys, Hcys, GSH 7: Cys, Hcys, GSH, MAA, MPA, MCE, NAC 3: Cys, Hcys, GSH 8: D/L-Cys, Hcys, GSH, MAA, MPA, MCE, NAC 8: D/L-Cys, Hcys, GSH, MAA, MPA, MCE, NAC 4: Cys, Hcys, GSH,

[77] [67] [123] [122]

Dyes Urease−metal ion pairs

4

fluorescence Absorbance

GSSG 6: Cys, GSH, MCE, Cm, DTT

MPA,

[124]

Abbreviations: DA: dopamine; Cys: cysteine; Hcys: homocysteine; MAA: mercaptoacetic acid; MCE: 2-mercaptoethanol; NAC: N-acetylcysteine; Cm: cysteamine hydrochloride; DTT: dithiothreitol

4. Conclusions The development of chemical “tongue” sensor array was quite exciting and interesting. From recent years, much efforts have been devoted form the design of sensing elements, the mechanism of recognition and the targets we would like to achieve. In view of applications, metal ions, amino acids, proteins and biothiols related to environment or clinic have been successfully discriminated in at least one approach. However, several unsolved problems should also be concerned when we concentrated on this field. The limitations of the data analysis we used. PCA was the most popular method in chemical “tongue” sensor array. However, it relies on the database we tested and built previously and the accuracy of it was obviously lower than those of conventional approaches. That means, according to the common situations, we choose several specific combinations or mixture components to mimic most of the possibility. Therefore, any tiny changes or interfering species could potentially induce great deviation from the plots. Meantime, when different samples (e.g. water sample from different lake or tissues samples from different patients) were tested, different database should be established indicating that there is a huge workload and time-consuming process for results. Besides, the contributions of chemical sensor array should not be ignored. Certain adverse effects on sensor are caused by poor training procedures, or by insufficient stability/reproducibility of the sensing parts. Therefore, it is necessary to consider the key features of the stability and/or reproducibility of the signals generated. No matter environmental pollution or diseases could not have only one factor to occur, so designing novel and fascinating “tongue” sensor array deep into mechanism was quite meaningful. Of great importance, by deliberate control between the sensor arrays and machine learning approaches, it is possible not only to detect and discriminate between the various environmental pollution or diseases but also to minimize the effects of primary demographic and environmental confounding factors [126]. Because of their intriguing features, we expect that the ideas regarding the integration of chemical “tongue” sensor arrays and revolutionary data processing (e.g. machine learning) could fundamentally research the interactions or reactions on the molecular level in the future.

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Highlights: Concept, mechanism and the recent progress of chemical “tongue” sensor array are reviewed. Design of chemical sensor array based on organic molecules, nanomaterials and organic-inorganic hybrid are listed and demonstrated. The applications of chemical sensor array related to metal ions, amino acids, proteins and biothiols are discussed.

The authors declare no conflict of interest.