Impedimetric transducers based on interdigitated electrode arrays for bacterial detection – A review

Analytica Chimica Acta xxx (xxxx) xxx

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Review

Impedimetric transducers based on interdigitated electrode arrays for bacterial detection e A review Sergi Brosel-Oliu a, Natalia Abramova a, b, Naroa Uria a, Andrey Bratov a, * a b


nica de Barcelona (IMB-CNM), CSIC, 08290, Bellaterra, Spain Departament de Micro-Nano Sistemes, BIOMEMS Group, Institut Microelectro Lab. Artificial Sensors Syst., ITMO University, Kronverskiy pr.49, 197101, St.Petersburg, Russia

h i g h l i g h t s

g r a p h i c a l a b s t r a c t


Review focusing on the latest application of interdigitated electrode array sensors.
Impedimetric transducers for bacterial detection.
Monitoring of bacterial metabolism.
Sensor with bacteria as a biorecognition element.

a r t i c l e i n f o

a b s t r a c t

Article history: Received 8 April 2019 Received in revised form 29 August 2019 Accepted 10 September 2019 Available online xxx

Application of the impedance spectroscopy technique to detection of bacteria has advanced considerably over the last decade. This is reflected by the large amount of publications focused on basic research and applications of impedance biosensors. Employment of modern technologies to significantly reduce dimension of impedimetric devices enable on-chip integration of interdigitated electrode arrays for lowcost and easy-to-use sensors. This review is focused on publications dealing with interdigitated electrodes as a transducer unit and different bacteria detection systems using these devices. The first part of the review deals with the impedance technique principles, paying special attention to the use of interdigitated electrodes, while the main part of this work is focused on applications ranging from bacterial growth monitoring to label-free specific bacteria detection. © 2019 Elsevier B.V. All rights reserved.

Keywords: Interdigitated electrode arrays Impedimetric sensors Bacteria detection Bacteria metabolism monitoring

Contents 1. 2. 3.

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Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Interpretation of impedance data and importance of equivalent circuits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1. Faradaic and non-faradaic impedance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Interdigitated electrode arrays (IDEA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. Equivalent circuit of IDEAs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Fabrication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Bacteria detection with impedance techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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* Corresponding author. E-mail address: [email protected] (A. Bratov). https://doi.org/10.1016/j.aca.2019.09.026 0003-2670/© 2019 Elsevier B.V. All rights reserved.

Please cite this article as: S. Brosel-Oliu et al., Impedimetric transducers based on interdigitated electrode arrays for bacterial detection e A review, Analytica Chimica Acta, https://doi.org/10.1016/j.aca.2019.09.026

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Impedance microbiology e impedimetric detection of metabolites produced by bacterial cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Detection of whole bacteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.1. Selective bacteria detection using different biorecognition elements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.2. Detection of bacterial components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.3. Indirect and non-selective bacteria detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3. Microbial based-biosensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Declaration of competing interest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . CRediT authorship contribution statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1. 4.2.

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1. Introduction Since 1962, when Leland C. Clark and Champ Lyons presented the first glucose amperometric biosensor based on glucose oxidase enzyme [1], electrochemical biosensors have become an object of intensive research. Compared to sophisticated and expensive traditional bioanalytical techniques, electrochemical biosensors based on amperometric, potentiometric or impedimetric transducers present themselves as cheap, sensitive, easy-to-use devices converting chemical information into a measurable electrical signal. In recent years biosensors employing impedimetric transducers received considerable interest [2] mainly due to their ability to perform label-free detection [3e5]. A wide range of different impedimetric biosensors have been reported [6] and the number of publications grows from year to year. However, better understanding of the fundamentals of these biosensors is required to achieve versatile analytical devices with a higher sensitivity and accuracy, better reproducibility and lower detection limits. This type of biosensors register changes in the interfacial electrical properties of a metal electrode affected by interactions between a biorecognition element attached to its surface and the analyte present in a sample solution. Depending on the type of biorecognition element, these devices permit monitoring of a wide range of analytes, with several advantages over other techniques, like small size, low cost, direct and fast response. Another positive feature of impedimetric biosensors is that, unlike amperometric or potentiometric devices, they do not generally need a bulky reference electrode to perform the measurements, which simplifies the experimental procedure and permits miniaturization of the sensor and the whole system. Electrochemical Impedance Spectroscopy (EIS) has been widely employed in different modes for bacteria detection and bacterial metabolism monitoring. Basically, sensing of bacteria using EIS technique may be performed in two ways: by detection of metabolites produced by bacterial growth that induce conductivity changes in the culture medium [7], or detecting the impedance changes caused by interaction of the target bacteria with the electrode surface [8,9]. Additionally, impedance can also be employed for monitoring variations in the ionic concentration and conductivity of the medium caused by the activity of enzymes used as labels for the signal amplification [10]. While performing impedance measurements in the presence of bacteria it is important to consider that biological cells are formed of composite biomaterial layers with differing electrical properties [11]. Thus, the cell membrane is highly insulating, while the cytoplasm in the interior of the cell is highly conductive. In that sense, another relevant aspect to take into consideration is impedimetric properties of bacterial cells [12]. Under application of an external electric field the presence of bacteria affects the overall impedance of the system. At low frequencies (Hz-kHz region) the electrical

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field will not permeate bacteria due to the isolating properties of their membranes, while at higher frequencies (several MHz), the field lines will partially penetrate through the membrane giving information of the cytoplasm properties. In addition, attachment of bacteria on an electrode surface directly affects the interfacial impedance. If bacterial cells remain intact after the immobilization onto an electrode the active area of the electrode will be affected. Thus, bacteria will obstruct the pass of the current producing an increase in the interfacial impedance [11,12]. Impedimetric biosensors for detection of bacteria may be formed using different kinds of electrode configuration. One of the most common systems applied for impedance biosensors is based on a three-electrode configuration [13]. Here, a working, an auxiliary and a reference electrodes are employed to measure the impedance of the electrochemical cell. In this case, the working electrode is functionalized with a biorecognition element to interact with bacteria. The exciting signal and the current is measured between the working and auxiliary electrodes, and the reference electrode allows controlling the DC bias applied to the working electrode. The auxiliary electrode is chosen with a large surface area to reduce its own impedance. This three-electrode configuration is mainly employed in faradaic mode measurements in the presence of a redox couple in the test solution. The reference electrode permits an accurate control of the working electrode DC potential to facilitate the redox process. Application of modern technologies for impedimetric sensor development permitted significant reduction of the sensors dimension, making use of two in-plane micro-band electrodes forming an interdigitated electrode arrays (IDEA), also named as interdigitated microelectrodes (IDME) [14]. In this case the current response to the applied AC signal is measured between the pair of symmetrical comb-like electrodes without applying additional DC bias. As both electrodes are commonly of the same material, it is assumed that under an open circuit potential, the difference between the electrodes is close to zero. This eliminates the need for a reference electrode. In this review the information provided is focused exclusively on publications dealing with interdigitated electrodes as the transducer unit. The use of interdigitated electrode arrays for biochemical sensing applications has gained increased interest during the last two decades, making IDEA one of the most commonly used electrochemical sensor structures [6]. Among the advantages of IDEAs are: easy-miniaturization, absence of the need for a reference electrode, rapid establishment of steady-state conditions in comparison to larger scale electrode systems and increased signal-tonoise ratio [14e16]. An additional advantage of this type of sensors is that they do not require markers for the detection of specific biomolecule analyte (label-free detection), as its interaction with the sensor surface produces electrical changes that can be monitored directly by means of impedance measurements. In the

Please cite this article as: S. Brosel-Oliu et al., Impedimetric transducers based on interdigitated electrode arrays for bacterial detection e A review, Analytica Chimica Acta, https://doi.org/10.1016/j.aca.2019.09.026

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literature IDEA sensors are usually classified as capacitive sensors because they allow to measure the changes in dielectric properties at the electrolyte-electrode interface [17]. However, interaction of IDEA sensors with analyte can also produce surface conductivity changes that affect impedance of this type of transducers [18]. One of the best reviews on interdigitated array microelectrodes based impedance biosensors for detection of bacterial cells was published nearly ten years ago [14]. More recent publications deal mainly with physical aspect of these devices [2], basic principles of impedimetric biosensors [19], new trends for the detection of bacteria with impedance-based methods [20,21], applications of new materials, like nanoparticles and magnetic beads [22], or new concept of impedimetric electrodes [23]. The purpose of this review is to focus upon recent reports on IDEA based impedimetric transducers for bacterial detection, for critically reviewing the field and marking the future trends. 2. Interpretation of impedance data and importance of equivalent circuits

Typically, more than one equivalent circuit model may fit the obtained experimental data equally well. This means that something should be known a priori about the electrochemical system under study in order to choose correct EC components that reflect the real physical-chemical phenomena occurring in the system. Moreover, to guarantee the correctness of the chosen EC, special experiments should be carried out, in which some of the system parameters, e.g. solution resistance or interfacial capacitance, remain fixed and some others vary, to see how it is reflected in the EC components values after spectra fitting. Each component of the EC gives its input into the total impedance depending on the applied frequency. Therefore, in complex systems the measurements are performed in a well-defined wide frequency range to simplify spectra interpretation. In some specific cases just one frequency may be selected to monitor an individual parameter of the EC. However, as it was noted above, real systems are quite complex and elaboration of a proper EC requires the profound knowledge of the system. 2.1. Faradaic and non-faradaic impedance

Electrochemical Impedance Spectroscopy (EIS) technique is used in a wide variety of applications, like material surface characterizations, corrosion process, electrode kinetics, membranes studies or fuel cell optimization [24]. During recent years many studies have been directed to the development of biosensors based on impedimetric transducers. This is due to the fact that EIS offers information on interfacial phenomena occurring on or close to the surface of a device, which is a powerful tool for characterization of sensors for biological targets. The impedance (Z) of a system is generally determined by applying an AC voltage (Vt) of small amplitude between working and auxiliary electrodes and detecting the resulting sinusoidal current (It). This AC current depends on the frequency and is characterized by its amplitude and phase (f). At each frequency value for the system under study the modulus of impedance, Z0 ¼ Vt/It, and the phase shift (f) between the voltage and current may be determined. Taking into consideration that the impedance is a complex value it can also be presented by its real and imaginary part:

Z ðuÞ ¼ Z0 ej f ¼ Z0 ðcosf þ j sinfÞ ¼ Zre þ jZim

3

(1)

Graphical representation of an impedance spectrum measured in a certain frequency range can be plotted as a Nyquist plot presenting the real part of the impedance (Zre or Z0 ) versus its imaginary part (Zim or Z00 ). In the Nyquist plot each point represents the system impedance at a single frequency. It is important to note that in order to prevent spectral distortion, both axes should be of the same scale, which is often not the case in many published papers. Another common mode to present an impedance spectrum data graphically is the Bode plot. In this case Z0 and f values are plotted on the Y-axis versus the logarithm of frequency (log f) on the X-axis. Both diagrams, the Nyquist and Bode plots, are typically employed to monitor the impedance changes occurring in an electrochemical cell and to evaluate the impedance response at different frequencies. From the experimental viewpoint, EIS is a very simple technique, which makes it rather popular. One of the most difficult parts of the EIS is correct interpretation of data from obtained spectra due to the complexity of physical, chemical or biological phenomena taking place in a system. Usually the spectra are analyzed using an equivalent circuit (EC), which is composed of different electrical components, combined in parallel or serially, representing the physiochemical properties of the studied system, in general modeled by resistances (R) and capacitances (C) [25].

EIS measurements with metallic electrodes in an electrolyte solution may be accomplished in two modes, in the presence of an additional redox probe used as a marker or directly in an analyte solution. In the presence of a redox pair in solution an electrochemical oxidation/reduction reaction takes place on the metal electrode surface and this impedance measurement mode is usually referred to as faradaic. In non-faradaic conditions the redox probe is not required [9]. Impedance measurements in the presence of electroactive compounds are widely described in the general electrochemistry literature. The equivalent circuit employed for experimental spectra fitting is known as the Randles EC, presented in Fig. 1A. This is a simple and well-known model used to present a faradaic process and is widely employed to describe the behavior of impedance-based biosensors [26]. It is formed by different elements: the solution resistance (RS), the double-layer capacitance (CDL), the charge-transfer resistance (RCT) and the Warburg impedance (ZW). The bulk properties of the electrolyte and the diffusion of redox probe are represented by RS and ZW, while CDL and RCT depend on the surface properties of the electrode/electrolyte solution interface. Depending on the applied frequency the impedance of the faradaic system may be limited either by kinetic or diffusion processes [11]. The Nyquist plot (Fig. 1B) is the best graphical approach to study the Randles EC elements. The semicircle corresponds to the electron transfer limited process at high frequencies, while the linear part represents the diffusion limited process at low frequencies. The intercept of the semicircle on the left side with the real axis (Zre) corresponds to RS, and the intersection of the semicircle on the right represents the sum of RS and RCT. The double layer capacitance CDL can be calculated from the frequency at the maximum of the semicircle (u ¼ 2 p f ¼ 1/RCT CDL) and the ZW by extrapolating the 45⁰ line observed in Fig. 1B. The ZW is conditioned by the Warburg coefficient (s), a complex parameter depending on the properties of the redox couple, geometrical features (the area of the electrode), and experimental conditions. It may be noted once again that to avoid distortion of the spectrum both axes should be of the same scale. In some analytical applications the effect of the ZW is neglected by selecting a frequency range where no diffusive response is observed in the Nyquist plot and interfacial and bulk properties are predominant. In the case of faradaic impedance, the main parameter to be monitored is the charge transfer resistance (RCT) (see Fig. 1B). The RCT is mainly affected by the kinetics of electron transfer from the

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Fig. 1. A) Randles equivalent circuit and B) corresponding Nyquist diagram.

electrolyte to the metal and depends on the properties of the redox pair (concentration of species, temperature and applied potential) and the structure of the interface. The use electron mediators, such as Fe(CN6)3e/4e (ferricyanide/ferrocyanide) or Ru(NH3)6 3þ/2þ (hexaammineruthenium III/II ions), at sufficiently high concentration guarantee that impedance does not become limited by the process of charge transfer between the redox pair and the electrode surface [27]. Modification of the electrode surface causes its blocking and affects the RCT. This phenomenon is widely used in impedimetric biosensors to measure concentration dependencies. In the case when a redox mediator is absent in the electrolyte solution the impedance is termed non-faradaic [28]. Without a redox pair the electron charge transfer is not produced and RCT becomes infinitely large. In the non-faradaic mode, a transition current flows across the surface of the electrode and mainly depends on electrode interfacial capacitance and the impedance of the surrounding solution, ZS (see Fig. 2A) This mode is considered more amenable for direct biosensing and point-of-care applications [5]. The impedance of the solution, ZS, is formed by two elements in parallel: the geometrical (or stray) capacitance, CS, between the electrodes in the electrolyte solution, and the electrical resistance

of the solution RS, which depends on conductivity of the medium. RS is also affected by temperature and geometry of the electrodes. However, in the case of large-scale electrode systems, CS values are typically high and its effect on ZS is negligible. That is why in the majority of systems, when the studies are focused on the solution conductivity changes, the ZS is simplified by RS. In the absence of a faradaic process the equivalent circuit is simplified to a serial combination of the solution resistance and electrode/solution capacitance and the useful signal mainly comes from the interfacial capacitance changes. This capacitance may be affected by the presence of absorbed species or the formation of molecular layers on the electrode surface. Moreover, when an electrode is immersed in an electrolyte solution an electrical double layer is formed at the electrode/solution interface defined as the double layer capacitance (CDL). Here it is important to note that there is an inaccurate use of the “double layer capacitance” term in numerous publications. CDL is always present at the electrolyte solution/solid interface and mainly depends on the electrolyte concentration. While in poorly conducting solutions with low ion concentration it may be affected by significant change of the electrical charge at the electrode surface, at high electrolyte concentration it will be invariable. The presence of organic molecules or

Fig. 2. Simplified equivalent circuit of an electrode in non-faradaic measurement mode (A) and Nyquist plot of the circuit impedance at different Constant Phase Element (CPE) a values typical for metal electrodes.

Please cite this article as: S. Brosel-Oliu et al., Impedimetric transducers based on interdigitated electrode arrays for bacterial detection e A review, Analytica Chimica Acta, https://doi.org/10.1016/j.aca.2019.09.026

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even bacteria at the sensor surface will result in additional layer with its own capacitance that is connected in series with the CDL. This combination may be correctly referred to as “interfacial capacitance”. Therefore, the interfacial capacitance modulated by the surface modifications may be used to monitor surface reactions on the electrode [7,25,27]. It is important to note that the impedance of the solid electrode/ electrolyte interface usually differs from purely capacitive behavior. Therefore, modelling the electrode/solution interface by an ideal capacitor with phase shift of f ¼ -90⁰ may result in poor fitting precision affecting the correct interpretation of data. Surface effects like the roughness of metal electrodes, surface inhomogeneity, etc. provoke this deviation from ideal capacitive behavior. For experimental spectra fitting of the interfacial capacitance the Constant Phase Element (CPE) [24] should be used, which is expressed as:

ZCPE ¼

1 ðj uÞa T

(2)

pffiffiffiffiffiffiffi In equation (2) j is the imaginary unit (j ¼ 1), u is the angular frequency (rad/s), a is an empirical constant representing the behaviour of the CPE, T is expressed in F$cm2$sa1 [24], from which the “average” double-layer/interfacial capacitance may be estimated. When the exponent a is equal to 1 the CPE behaves as a pure capacitor. If the value of a becomes 0 the CPE will behave as a resistor. Typically, a for metal electrodes fluctuates between 0.7 and 0.98 [6]. An example of the impedance response of a serial R-CPEDL combination at different a values is shown in Fig. 2B. To sum up, for an accurate interpretation of the impedance data, it is important to appropriately choose an equivalent circuit model that reflects the physical, chemical or biological phenomena at the electrode surface. 3. Interdigitated electrode arrays (IDEA) As previously noted, configuration of electrodes into an interdigitated structure permits to miniaturize impedimetric transducers, integrating both electrodes in a single chip, and apply highly scalable microelectronic manufacturing technology for their fabrication. In the case of IDEA devices, the transducer geometry is of a crucial importance for sensitivity enhancement taking into consideration that the current flows mainly close to the sensor surface presenting a higher sensitivity to surface changes compared with other designs. A planar IDEA sensor presented schematically in Fig. 3A and B, is formed by a pair of comb-like electrodes on an insulating substrate. Contact pads are used for wiring. The sensor geometry is characterised by the number and length of the electrode digits, their width (w) and interdigital spacing (s). Penetration of the electric field under applied potential is approximately equal to the distance between the centres of the electrode digits (w þ s), so the current flows close to the sensor surface [29]. Thus, the miniaturization of the electrode width and the spacing between the electrodes allows to increase the sensitivity related with reactions occurring on the sensor surface. 3.1. Equivalent circuit of IDEAs Due to the fact that IDEA electrodes are typically symmetrical, of the same size and made of the same material the impedance measured between them is the sum of the impedance of each individual electrode that forms the digits. A typical Nyquist and Bode plots and the corresponding simplified equivalent circuit employed for the interpretation of the impedance spectra of an IDEA in nonfaradaic mode is presented in Fig. 4.

5

The elements of the EC are: RC, the contact resistance of wires, contacts and collector bars; CG, the geometrical capacitance between the two electrodes connected by the electrolyte solution; RS, the electrical resistance between the electrodes introduced by the surrounding solution, and the CDL, the double layer capacitance at the electrode/solution interface. Additionally, the introduction of a biomolecule layer on the IDEA surface may result in an additional capacitance (CF) in series with the double layer capacitance. However, the combination of CDL and CF can be fitted by a single CPEDL. As previously detailed, the roughness of the metal electrodes, but also the introduction of additional layers may affect the CPE parameters. A semicircle observed in the Nyquist plot at high frequencies is associated with the parallel combination of CG and RS. The intercept with Z’ axis on the left side gives the RC value, and the intercept on the right side corresponds to the value of RC þ Rs. The linear response at low frequencies in the Nyquist plot is dominated by the CPE representing the electrical double layer capacitance. In previous studies [30,31], it has been demonstrated that RS, which represents the resistance between the IDEA electrodes determined from impedance spectra, should be treated as a parallel combination of the bulk solution resistance (RBULK) and the surface resistance (RSURF). The effect of RSURF on RS will be higher the higher is the bulk solution resistance. In low conductivity solutions the solution bulk resistance can be experimentally fixed, then any changes in RS can be attributed to RSURF variations. Therefore, the IDEA sensor response in controlled low conductivity solutions allows monitoring the changes in the surface charge due to the reaction with charged species. Taking into account that bacterial cells, as well as large biomolecules, in water solutions are electrically charged, modification of the spacing between the electrode digits with a bioreceptor molecule will permit to register its interaction with an analyte as the change in the surface charge density and, respectively, the surface conductivity. If, on contrary, only metal electrode digits are modified with biomolecules, interaction with analyte will produce changes only in interfacial capacitance. The resulting impedance signal in this case will only depend on the two electrodes surface area. The same result may be obtained using just two large in-plane electrodes of the same surface area. The advantages of the IDEA geometry are not exploited in this case. The same is true when IDEA sensors are used in faradaic impedance measurements. Here, once again, the resulting signal of charge transfer resistance will depend only on the electrodes surface area and IDEA geometry is not really necessary. 3.2. Fabrication Interdigitated structures with different kinds of metal electrodes are formed on an insulating substrate [32], like glass, oxidized silicon surfaces or polymers, using of microfabrication techniques and lithography process that permit to miniaturize the dimensions of the sensors. Silicon wafers covered with a thick oxide layer are the most commonly used substrates for IDEA fabrication. The first step of IDEA sensors fabrication is the formation of insulating silicon dioxide layer on a silicon wafer, isolating the silicon from the following deposition of metals [33]. The second step is the deposition of a highly conductive material employed for the formation of the electrodes. Among materials that are typically used for IDEA electrode formation are gold, platinum, indium-tin oxide (ITO) and tantalum silicide (TaSi2). The choice of TaSi2 instead of other traditional noble metals like gold or platinum is conditioned by the contaminating nature of these metals in standard complementary metal-oxide-semiconductor (CMOS) processes employed for the fabrication of the devices.

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Fig. 3. Planar interdigitated electrode arrays (IDEA) (A) and its cross-section (B), and 3D-IDEA (C) and its cross-section (B, D).

Fig. 4. A) The Nyquist and B) Bode plots of the impedance of IDEA sensors measured in low conductivity KCl 105 M solution and C) the electrical equivalent circuit.

The following phase is the photolithographic step to define the collector bars and digits of the two coplanar electrodes. The patterning of electrodes is carried out by means of reactive ion

etching technique, chemical etching or a lift-off process. The sensors geometry and electrode dimensions are defined by design of a mask used for photolithography.

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In the last years, novel geometries and designs for IDEA have been presented. To increase the sensitivity to surface charge registration Bratov and co-workers [34,35] proposed to separate the electrode digits of an IDEA using SiO2 insulating barriers to enhance the effect of surface conductivity on the impedance measurements. This design with insulating barriers is named as a three-dimensional interdigitated electrode array (3D-IDEA). In the case of IDEA sensors, the effect of the solution resistivity on the overall impedance relies on the depth of penetration of the electric field into the bulk solution, which depends on the width of the electrode digits and spacing between them. Thus, for a planar and 3D-IDEA with identical geometry of the electrode digits, the effect of the solution resistivity will be nearly the same. However, in the presence of insulating barriers the current path along the SiO2 surface is much longer in the case of 3D-IDEA, which permits to increase the sensitivity of the device to surface conductivity changes and, as a result, to easily monitor the surface modifications. More detailed information on this effect may be found elsewhere [30,31,33]. It may also be noted that the presence of barriers reduces the effect of a possible sensor surface contamination, because the electrodes digits are electrically separated and conducting microparticles deposited on the surface from surrounding ambient do not cause short-circuiting. Barriers of different height may be formed between the adjacent electrodes. Some studies evaluate the sensitivity of sensors using various barrier heights and the same width of the barrier and the electrode digits. The analysis of the sensors response demonstrated that devices with 4 mm barriers are highly sensitive [34]. An example of standard IDEA and 3D-IDEA devices of 3 mm width (w) and spacing (s) between electrode digits are presented in Fig. 3. Fabrication of the 3D-IDEA involves additional step of the barrier formation, in which a silicon dioxide layer is formed on a wafer between the interdigitated electrodes. The SiO2 layer is treated by deep ion reactive etching (DRIE) through a suitable mask to open the electrode digits and contact pads. Optical microscopy and scanning electron microscopy (SEM) images of flat and 3D-IDEA are shown in Fig. 5. 4. Bacteria detection with impedance techniques The use of interdigitated electrodes as impedimetric transducers allows to develop different systems for bacteria detections. As previously mentioned, sensing of bacteria using EIS may be performed by the detection of metabolites produced by bacterial growth or by detection of impedance changes caused by interaction of bacteria or bacterial components with specific biorecognition molecules immobilized on the surface of a transducer [14,36]. In addition, another possibility is the use of the bacteria cells as biorecognition elements for detection of other analytes to form microbial-based biosensors. In the following sections different strategies are widely discussed. 4.1. Impedance microbiology e impedimetric detection of metabolites produced by bacterial cells Impedance microbiology is a quantitative and qualitative technique that permits to control the bacterial growth which is monitored as changes in impedance between a pair of metal electrodes submerged into a growth medium or solution [37]. The bacterial metabolism provokes the conversion of large organic compounds (mainly carbohydrates transformed by catabolic pathways) to small products, like organic acids and carbon dioxide, by means of biochemical reactions. These metabolites of ionic nature released into the medium generate changes in its ionic composition and the

7

consequent alterations in the conductivity. Therefore, these variations may be correlated with microbial growth to determine the concentration of bacteria. This growth-based impedance method allows to differentiate between viable and dead bacteria cells since only live bacteria present metabolic activity with the consequent change of the medium composition. Therefore, impedance microbiology is considered as a rapid method for detection of bacteria, mainly attributed to detection of foodborne pathogenic bacteria [11,38e40]. Based on this principal different commercial instruments have been developed for impedance microbiology analysis. The most common are Bactometer (Bio Merieux, Nuertingen, Germany), Malthus systems (Malthus Instruments Ltd., Crawley, UK), rapid automated bacterial impedance technique (RABIT system) (Don Whitley Scientific Ltd., Shipley, UK), or more recent BacTrac (SyLab, Purkersdorf, Austria) [11,37,41,42]. These systems have been validated in comparison with other standard methods, and are commonly used in food quality analysis, as well as for the evaluation of selective mediums for bacterial growth [43e51]. The impedance changes registered with metal electrodes in a growth media may be caused by two factors. As previously mentioned, the first one is the microbial metabolism, that affects the conductivity of the medium due to the conversion of highmolecular weight nutrients into smaller charged ionic components [37]. In parallel, the electrode interfacial impedance can be also altered by the adhesion of bacteria to the surface [52] affecting the capacitance of the electrode/solution interface. Depending on the frequency range in which the measurements are performed the impedance will be conditioned by the conductance of medium, known as the electrolyte impedance, or the interfacial impedance, affected by the electrode/electrolyte interface. The superficial impedance of the electrode is predominant at low frequencies, while the solution/medium resistance of the system affects the system impedance at high frequencies [11]. Therefore, the growth of microorganisms may result simultaneously in the increase of conductance and capacitance, causing a decrease in the overall measured impedance [53]. It is clear that the impedance response will depend on the electrode dimensions, as well as the spacing between two electrodes. Additionally, since changes are produced by metabolic activity of the cells, other parameters, like the temperature or pH, should to be strictly controlled during the microbial growth to obtain reproducible results. The composition of the medium is another essential parameter to consider in the impedance microbiology studies. The culture medium not only guarantees the bacterial growth but also acts as the supporting solution in which changes of electrical properties are occurring. In terms of impedance measurements, to obtain higher sensitivity to the changes in the ionic composition produced by bacteria it is required to perform experiments in a growth medium with low intrinsic conductivity. For this reason, in the last years the research in this field has been focused on the design of selective media with low conductivity [39,50,54]. In impedance microbiology a minimum initial concentration of bacteria is required to observe perceptible changes in the measured impedance. The typical bacterial growth curve plotted in relation to the incubation time is graphically presented in Fig. 6 in comparison with the impedance growth curve. To sum up, microbiological impedance depends on different parameters, such as the type microbial species, initial number of microorganisms, the temperature, pH and composition of the supporting solution (the medium) employed. The resulting impedance will also depend on the frequency range of the applied signal and the electrode properties (dimensions, material, geometry and spacing) [55]. To provide the selectivity for a specific target bacteria particular antibiotics may be introduced into the culture

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Fig. 5. Optical image of IDEA surface (A) and SEM images of interdigitated electrode fingers of a planar IDEA (B) and of a 3D-IDEA with 4 mm barriers (C).

Fig. 6. Impedance changes represented as the microbial impedance growth curve (red line) compared with a classical bacterial growth curve (dashed line) in time with the corresponding growth phases (Adapted from Ref. [27], copy right belongs to the authors). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

media [48]. Among different types of electrodes for monitoring the growth of bacteria, interdigitated array microelectrodes have been demonstrated effective in impedance measurements, especially in small sample solution volumes due to their dimensions [54,56]. Utilization of microelectrodes allows controlling the bacterial metabolic activity by means of impedance measurements, increasing the sensitivity, minimizing sample volume and reducing the required assay times [11]. However, a limited number of publications, which are presented in Table 1, related to the impedance microbiology employing IDEA devices appeared in the last years. One of the examples is the work of Varshney and Li [54], in which a microfluidic flow cells with incorporated IDEA sensor is

used to achieve a fully integrated microchip to enhance and facilitate the microbial growth sensing. This brings different benefits such as high detection sensitivity, small volume handling, low contamination during bacterial growth, ability to concentrate cells, and rapid detection of small number of cells [54]. The reported flow system with double interdigitated array microelectrodes permits to detect viable cells of E.coli O157:H7 monitoring the impedance at a frequency of a 1 MHz. Changes in the impedance are attributed to the decrease in the resistance of the medium due to an increased concentration of highly charged ions produced during the growth of the bacteria in a low conductive medium. The system may be successfully employed for the E.coli O157:H7 detection in a range from 8 to 8.2$108 CFU/mL after 14.7 and 0.8 h of cultivation time, respectively. Liu et al., in 2015 [60] presented an impedance sensor for E. coli detection in milk samples. In this study, interdigitated microelectrodes were used to measure the impedance changes at low frequencies (1 Hze1 KHz) in a growth medium and milk samples affected by bacterial metabolism. Here, impedance changes were attributed to changes in the sensor interfacial capacitance showing dependence of both the growth time and the initial concentration of E. coli. Thus, the sensor was able to detect E. coli concentrations between 7.2 and 7.2$108 cells/mL in 10.6e1.4 h respectively [60]. Bacteria metabolic products are of acidic nature, like acetic or lactic acid, thus, the produced conductivity changes due to ionic products are accompanied by pH changes of the growth media [63] that correlate with bacteria concentration [64]. Uria et al. [61] performed experiments with an interdigitated electrode array showing that changes of E. coli concentration in the growth medium provoke changes of impedance measured at a fixed frequency of 10 kHz. Possible changes in the impedance magnitude due to bacteria attachment to the electrode surface were avoided by carrying out a single measurement after a certain incubation time of E.coli, when a drop of the growth media was placed on a sensor surface. Taking into consideration that the kinetics of impedance

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Table 1 Application of IDEA sensors in impedance microbiology technique for bacteria metabolism monitoring. Growth medium

Electrode material (Measurement frequency)

Limit of detection

Detection time (h)

Year

Reference

Tris-Glya buffer þ dextrose

Platinum (11.43 kHz)

107 -108 cell/mL

2

2002

[39]

SC/TM/Ma BHIa YPLTa LBa LBa/Milk LBa/Milk BHIa Agar

Indium-tin-oxide (ITO) (10 Hz) Indium-tin-oxide (ITO) (10 Hz) Gold (1 MHz) Golds (1 kHz and 10 kHz) Gold (10 Hz) Platinum (10 kHz) Gold e Nickel (38 kHz)

4.8-5.4$105 CFU/mL 10e106 CFU/mL 8e8.2$108 CFU/mL e 7.2e7.2$108 cell/mL 102e106 CFU/mL 104-106 cell/mL

9.3e2.2 8e1.5 14.7e0.8 6 10.5e2 6e2 ~1

2004 2006 2008 2013 2015 2016 2019

[57] [58] [54] [59] [60] [61] [62]

Target microorganism Listeria innocua Listeria monocytogenes E.coli Salmonella typhimurium Salmonella typhimurium E.coli O157:H7 Escherichia coli DH5a E.coli E.coli E.coli

a Tris-Gly: Buffer Tris-Glycine; SC/TM/M: Fluid selenite-cystine broth (SC) þ TMAO$HCl (TM) þ Manitol (M); BHI: Brain Heart Infusion Broth; YPLT: Yeast-Petone-LactoseTMAO; LB: Luria-Bertani Miller's Broth.

changes in time is not linear and depends highly on an initial bacteria concentration, a novel calibration method was employed measuring the sensor response at 270 and 390 min of incubation and taking a mean value [61]. This permitted obtaining the calibration curve with nearly the same sensitivity between 102 to 106 CFU/mL of bacteria concentration. Finally, the proposed calibration method employing impedimetric sensors was demonstrated to be useful for quantifying E. coli bacteria in milk from 102 and 106 CFU/mL in only 6 h. Additionally, in a recent work, Butler and collaborators [62] developed a label-free sensor using 3D metal microelectrodes integrated with an agar growth medium to detect the metabolic activity of E. coli cells in small volumes of 1 mL. The resulting microsystem allows to selectively identify live cells in a wide liner range (104-106 cells/mL) in just 1 h. However, no practical application was experimentally demonstrated. Summarizing, it can be concluded that the impedance microbiology is a well-established method for bacteria growth control and monitoring employed in the last decades that have been gradually improved by employing novel microfabrication techniques to develop impedimetric sensors in a chip-based format. However, the limited number of publications related to this technique in the recent years shows the inclination of the research to different and more complex strategies, such as functionalization of sensor surfaces and the use of nanomaterials, and also novel strategies to differentiate between live and dead cells [65e68].

4.2. Detection of whole bacteria Bacterial cells can also be detected by means of their interaction with the surface of an impedimetric transducer. The reduction of the effective electrode area of interdigitated electrodes due to the bacterial attachment affects the electrolyte/electrode interface. In the case of faradaic impedance measurements, the presence of bacteria attached to metal electrodes affects the charge transfer resistance, RCT, of the electron transfer from the redox pair to the metal electrode. In the non-faradaic measurement mode, the interfacial capacitance will be mainly affected due to the presence of absorbed species or the formation of additional layers on the electrode surface. This capacitance of the adsorbed species is in series with the electrical double layer capacitance (CDL), that mainly depends on the ionic concentration in water solution, both contributing to the total interfacial capacitance that can be determined from the impedance spectra. Impedimetric IDEA sensors used for selective bacterial detection may be classified according to the type of biorecognition elements immobilized on the surface of the electrode to enhance the specificity for a particular bacterial cell. In some cases, like biofilm

growth monitoring, the specificity of a bacteria sensor is not important and IDEA devices may be used to control non-specific attachment of bacteria cells to the sensor. 4.2.1. Selective bacteria detection using different biorecognition elements Most of the studied impedimetric biosensors employ biorecognition elements immobilized on their surface which selectively react with a specific target analyte (bacteria) forming a complex that alter the electrical properties of the sensor. Different bioreceptors employed in IDEA-based biosensors for bacteria detection are presented in Table 2. The majority are of the family of affinity biomolecules, like antibodies, nucleotide-based molecules of DNA, RNA or aptamers, while other receptors include bacteriophages, lectins and antimicrobial peptides. Various strategies are used to promote immobilization of biorecognition elements on IDEA transducers: bioaffinity layers, Langmuir-Blodgett films, thiol containing self-assembled monolayers on gold (SAMs), chemical grafting by silanization, layer-by-layer deposition of polyelectrolyte films, etc. [25,69e72]. The selection of the appropriate bioreceptor has to be evaluated taking into consideration different aspects, like the biomolecule chemical nature, reproducibility of its properties, like activity and purity, production cost, and difficulty of immobilization. After immobilization the biomolecules should be strongly attached to the sensor surface preventing their desorption during the use of biosensor, maintaining their active structure, functionality, high sensitivity and selectivity, fast reaction kinetics, and high stability [73,74]. In addition, depending on the strategy employed the biorecognition element can be immobilized on the metal electrode, within the space between digits (the insulating substrate) or on the entire surface. 4.2.1.1. Antibodies. A large number of works published in the last years are devoted to immunosensors with antibodies as biorecognition elements immobilized on the surface of interdigitated electrodes. One of the first works was published by Yang et al. [9] presents an impedimetric biosensor for detection of Escherichia coli O157:H7 with antibodies immobilized on an IDEA sensor with indium-tin oxide (ITO) electrodes. The measurements were carried out in a Faradaic mode in the presence of ferri/ferrocyanide redox pair and the spectra were fitted with a common Randles equivalent circuit. The capture of E. coli cells produced the increase in the charge transfer resistance, which correlated with the bacterial concentration in a range from 4.36$105 to 4.36$108 CFU/mL. The sensor showed the detection limit of 106 CFU/mL. However, as previously mentioned, the use of interdigitated electrodes in the case of Faradaic measurements does not add any advantages. Lately, Radke and Alocija [75] functionalized the silicon dioxide surface

Please cite this article as: S. Brosel-Oliu et al., Impedimetric transducers based on interdigitated electrode arrays for bacterial detection e A review, Analytica Chimica Acta, https://doi.org/10.1016/j.aca.2019.09.026

Biorecognition element Antibodies

Target bacteria or bacterial components

IDEA material

Site of immobilization Application (M and/or O)a

Detection Limit of detection time (range of application)

E. coli O157:H7 E. coli K12

Indium-tin oxide (ITO) Gold on silicon dioxide

MþO O

Detection of bacterial cells Detection of bacterial cells

e e

E. coli O157:H7

Gold on silicon dioxide

O

e

Salomenlla enteritidis

Gold on silicon dioxide

M

E. coli K12 and Salmonella typhimurium E. coli JM109 E. coli K12

Gold on glass substrate

MþO

Detection of bacterial cells in food samples (lettuce) Detection of foodborne pathogens Detection of bacteria

Conductive polysilicon

MþO

Gold on quartz glass

M

Staphylococcus aureus

Aluminum (covered with Al2O3)on silicon dioxide

MþO

E. coli O157:H7

Gold on silicon dioxide

MþO

Legionella pneumophila

ITO on glass

MþO

E. coli O157:H7 E. coli DSMZ 17076 Enteropatho-genic Escherichia coli E. coli O157:H7

Gold on glass Conductive polysilicon Silicon carbon alloy

M MþO MþO

Graphene with gold

M

Salmonella typhimurium

Gold on silicon dioxide

M

Cholera toxins E. coli O157:H7 (E. coli DSMZ 17076) E. coli DH5a

Gold on silicon dioxide TaSi2 electrodes on silicon dioxide Gold

M MþO

Gold on silicon dioxide

MþO

Gold on silicon dioxide Gold on silicon dioxide

MþO M

Detection of foodborne pathogens Detection of foodborne pathogens Detection of cholera toxins Detection of bacteria in water samples Detection of bacteria and LPS Detection of bacteria and compere Ab and phages as bioreceptors Detection of bacteria Detection of bacteria

Graphene with gold

M

Bacteria detection in saliva

Gold on silicon dioxide

M

Streptococcus sanguinis

TaSi2 electrodes on silicon dioxide

MþO

Detection of bacteria in water Detection of bacterial in saliva

E. coli

TaSi2 electrodes on silicon dioxide TaSi2 electrodes on silicon dioxide

MþO

Bacterio-phages E. coli K12

AMPs

Lectins

E. coli K12 E. coli ATCC 35218, E. coli O157∶H7, S. typhimurium, and L. monocytogenes Staphylococcus aureus and Helicobacter pylori E. coli ATCC 25922

E. coli lipopolysaccharides/ endotoxins

a

Selective Detection of Live/ Dead pathogens Propose a quantitative estimation model of bacteria captured Demonstrate the use of interdigitated array microelectrode for detection of bacteria Detection of bacteria in food samples Detection of Legionella in cooling towers Detection of bacteria Detection of bacteria Develop a new testing IDEA

(M ¼ , metal, O ¼ oxide).

M

MþO

Detection of bacteria in liquid samples Detection of bacterial endotoxins and new blocking method development

Supporting solution//medium

Reference

(105e107 CFU/

Redox probe [Fe(CN)6]3-/4-) 0.1% peptone water

[9] [8]

(104e107 CFU/

0.1% peptone water

[75]

in PBS and in milk (E. coli) and (Salmonella)

PBS and milk

[110]

PBS

[111]

Glycine buffer

[112]

1h

106 CFU/mL 105 CFU/mL mL) 104 CFU/mL mL) 104 CFU/mL 105 CFU/mL 104 CFU/mL 105 CFU/mL 1 cell

e

103e106 CFU/mL

PBS

[113]

10 min

e

Distilled water

[114]

e

3  103 CFU/mL

Grape and spinach samples

[115]

3 min 40 min

5

8

1h

From 10 to 10 CFU/mL

PBS

[116]

45 min 30 min e

3  102 CFU/mL e e

Distilled water KCl Luria-Bertani (LB) medium

[117] [118] [119]

30 min

10-100 cells/mL

PBS

[120]

1h 1h 30 min 30 s 60 min

2

6

10 CFU (76e7.6  10 ) in 50 mL 2 mg/mL 2.9  102 CFU/mL 267 cells/mL (102 e106 cells/mL) 104 CFU/mL (104e107 CFU/ mL)

Redox probe [Fe(CN)6]

3-/4-

) in PBS [121]

Redox probe [Fe(CN)6]3-/4-) in PBS [109] KCl 105 M [23] Distilled water

[81]

PBS and mineral water

[85]

60 min e

103 CFU/mL 103 CFU/mL

PBS PBS

[86] [90]

e

(103e108 CFU/mL)

Distilled water

[122]

PBS and water samples

[91]

KCl 105 M

[92]

20 min

102 CFU/mL (102e106 CFU/ mL) 3.5  101 CFU/mL in KCl 105 M and 8.6  102 CFU/ mL in artificial saliva 104 CFU/mL

KCl 105 M

[73]

20 min

2 mg/mL

KCl 105 M

[108]

1h

S. Brosel-Oliu et al. / Analytica Chimica Acta xxx (xxxx) xxx

Aptamer

10

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Table 2 Types of a biorecognition elements used in the development of impedimetric biosensors based on IDEA transducers for bacteria detection.

S. Brosel-Oliu et al. / Analytica Chimica Acta xxx (xxxx) xxx

between the gold interdigitated electrodes with polyclonal antibodies specific to E. coli O157:H7. The resulting biosensor was tested with bacteria suspensions in pure cultures and food samples, with a limit of detection of 104 CFU/mL and 107 CFU/mL respectively. The specificity of the proposed biosensor was also demonstrated in presence of non-target organism like Salmonella infantis. Though an equivalent circuit model with bacteria cells located between the electrodes was proposed, it was not tested and confirmed experimentally. In this case, no spectra are presented and only the impedance at three different frequencies is given, which makes it impossible to elucidate the effect of bacteria attachment on surface electrical properties. Publications on the development of IDEA-based immunosensors for bacteria detection are increasing year by year as it is reflected in Table 2. The main efforts of new studies are focused on the reduction of detection time and the limit of detection, as well as on the possibility to use this type of sensors in more complex real samples. Despite the fact that antibodies are the most used bioreceptors in biosensor research, their high production and purification costs limit their practical application. Another problem is their stability that affects the binding efficiency [28]. All these have provoked in the last years an intensive search for alternative biomolecules. In this sense, aptamers may be regarded as a plausible substitutes of antibodies for biosensing applications due to their high stability and ability to bind with high selectivity specific target molecules. Biosensors using aptamers as bioreceptors have been named as aptasensors [76]. 4.2.1.2. Aptamers. Aptamers are short oligonucleotides of RNA or DNA single-strand sequences between 30 and 100 nucleobases produced in vitro and with high affinity to their targets. These biomolecules are more stable than antibodies and are attractive due to the lower production costs, especially once the specific sequence is obtained [77]. Aptamers are typically folded in a specific three-dimensional structure allowing selective interaction with the corresponding molecule [78,79]. However, variations in shape and conformation of aptamers after immobilization may affect their binding affinity resulting in a low or lack of interaction with the analyte. Brosel-Oliu et al. [23] developed an IDEA-based biosensor for detection of E. coli O157:H7 using a DNA aptamer which recognizes the outer membrane proteins of this pathogenic bacterium and 3DIDEA as the impedimetric transducer. The aptasensor showed a linear response (R2 ¼ 0.977) proportional to the logarithm of bacterial concentration present in the sample, with the limit of detection of about 102 CFU/mL and a short detection time of only 30 min. Selectivity was demonstrated over other bacterial strains (E. coli K12, Salmonella typhimurium and Staphylococcus aureus). Moreover, the sensor regeneration methodology was developed allowing to employ the aptasensor multiple times, an essential feature to reduce costs per assay [80]. However, in the case of biosensor applications in real samples the main limitation is the sample matrix effect. Possible solution to this is to use a filtration system with posterior bacteria recovery to perform detection assays under more favorable conditions. Another recent work [81] demonstrated the applicability of a capacitive aptasensor for labelfree detection of E. coli. Here the aptamer was selected against the lipopolysaccharides of E. coli as gram-negative model bacteria and immobilized on commercial microelectrodes. 4.2.1.3. Bacteriophages. Other type of biorecognition elements that may be successfully employed for detection of bacteria are bacteriophages. Bacteriophages (or phages) are viruses with either narrow or broad specificity, which infect certain host bacteria being

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ubiquitous in almost all environments [17,20]. Their application in biosensors for bacterial cell detection is favorable because they offer a very high selectivity towards their host bacteria. Bacteriophages are easy to produce and are resistant to harsh conditions like high temperatures or organic solvents. They possess diverse functional groups on their surface which facilitate their immobilization on different kind of transducers [82]. One of their main characteristics is that phages can discriminate between viable and non-viable bacterial cells because they reproduce themselves only in living cells [83]. Although phages are generally easy to produce in large quantities, their purification is still quite expensive. Therefore, their cost as recognition elements is still too high and have to be more studied [84]. A few works have been focused on the use of IDEA and bacteriophages for bacteria detection. Mejri and collaborators [85] compared the response of sensors with antibodies and phages immobilized onto interdigitated gold microelectrodes. T4-phages, which specifically infect E. coli bacteria, were immobilized by physisorption on the sensor. In this work it was concluded that using the same sensor configuration the sensitivity in the case of phages was higher in comparison to antibodies. Moreover, a dual signal response was observed; firstly, an increase in the impedance due to bacteria cells attachment to the surface with the bacteriophage occurs and, secondly, a decrease is registered induced by the lytic effect of phages. The impedance variation showed a linear response for E. coli concentrations ranging 104e107 CFU/mL and a limit of detection of 104 CFU/mL. The specificity was also demonstrated using Lactobacillus as non-target bacteria. Lately, Baccar et al. [86] integrated interdigitated electrode arrays functionalized with T4-phages for detection of E. coli in a microfluidic cell to reduce the sample volume. In this case the detection of limit was reduced one order of magnitude, down to 103 CFU/mL. 4.2.1.4. Antimicrobial peptides (AMPs). Other interesting family of alternative bioreceptors is antimicrobial peptides (AMPs). AMPs are members of the innate immune system of many organisms capable to kill a wide range of pathogens, from gram-positive and gram-negative bacteria to viruses, fungi and even cancerous cells [87,88]. In general, positively charged AMPs by electrostatic forces react with negatively charged compounds, like lipopolysaccharides (LPS) of bacterial membrane, resulting in pore formation, membrane disruption and cell lysis [89]. AMPs may be synthesized with different chemical terminal groups for their chemical grafting onto a sensor and due to their small size (10-50 amino acids groups) permit to obtain high densities on the sensor surface. However, their main limitation in biosensing is the lack of selectivity for detection of different types and strains of bacteria. The work of Manoor et al. [90] is the first report on the use of AMPs on interdigitated electrodes as impedimetric sensors for bacteria detection. In this case, the AMP magainin I was immobilized on gold electrodes and the biosensor was exposed to various bacteria concentrations ranging from 103 to 107 CFU/mL. The variation in impedance at a fixed frequency of 10 Hz was directly proportional to the number of bacterial cells bound to the immobilized AMPs. The limit of detection of this biosensor to E. coli was 103 CFU/ mL (1 bacterium/mL), and other bacteria were also tested (E. coli O157:H7, E. coli ATCC 35218, Salmonella typhimurium and Listeria monocytogenes) to demonstrate its specificity. Later developed a biosensor using the AMP colicin V (ColV) as the biorecognition element to detect E. coli in water samples with a limit of detection of 102 CFU/mL [91]. The use of AMPs for detection of periodontopathogenic bacteria has been recently reported by Hoyos et al., 2016 [92]. The strategy employed consists in immobilization of a lactoferrin-derived peptide on 3D-IDEA impedimetric transducers. The developed sensor

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allows to detects Streptococcus sanguinis, a primary colonizer especially important in the formation of oral biofilms, in low conductivity solutions (KCl 105 M) with a limit of detection of 3.5$101 CFU/mL and 102 CFU/mL in a model artificial saliva solution within 1 h. 4.2.1.5. Lectins. Finally, another group of biorecognition elements described in the literature that can be used for the detection of bacteria are lectins, carbohydrate-binding proteins that are able to specifically react with the carbohydrates present on the surface of bacterial membranes. Their small size allows obtaining high densities of carbohydrate-sensing elements on a sensor surface, leading to higher sensitivity and lower nonspecific adsorption [93]. They are rather easy to produce compared to antibodies and have intrinsic stability [87]. Nevertheless, the main disadvantage of lectins is that one lectin can interact with different carbohydrates. Therefore, lectin-based biosensors show reduced selectivity that limits their application in complex samples with different bacterial targets. One of the most studied lectins is concanavalin A (Con A) which was widely employed in the development of biosensors for detection of bacteria [93e95], viruses [96] or cells [97]. Lectin-based sensors for bacteria detection are quite common, but the majority of reported studies use a three-electrode configuration to perform measurements in faradaic mode [95,98]. In the case of interdigitated electrode arrays, Brosel-Oliu et al., 2015 [73] developed a biosensor based on an interdigitated electrode array using the layer-by-layer method to assemble Con A as bioreceptor with polyethyleneimine as the anchoring layer. The authors reported the possibility to detect concentrations of E. coli around 104 CFU/mL in liquid samples. In a more recent work, Li et al. [99] proposed an impedance immunosensor with screen-printed interdigitated microelectrodes and wheat germ agglutinin (WGA) lectin for signal amplification for E. coli O157:H7 detection. WGA was added to enhance the signal taking advantage of the abundant lectin-binding sites on the bacteria surface. The reported sensor showed a LOD of 102 CFU/mL with a linear response range from 102 to 107 CFU/mL and a detection time of around 1 h. 4.2.1.6. Molecularly-imprinted polymers (MIPs). In order to improve the detection of different bacterial targets and develop easy-to-use robust biosensors, it is essential to focus the research on design of novel biorecognition elements for real applications. In the last years, attempts to use of engineered biomolecules like molecularlyimprinted polymers (MIPs) as substitutes of antibodies were reported [100,101]. MIPs are synthesized by polymerization of monomers in a mixture with cross-linkers and in the presence of template molecules that are the target analytes. Afterwards the template molecules are removed and the recognition sites are formed in cavities of a MIP polymer matrix with optimal shape, size and functional groups to capture the desired molecules and mimic the biological activity of natural bioreceptors. However, their use in different biosensing platforms is still limited due to the difficulty to avoid unspecific interactions produced by the heterogeneity of the imprinted cavities. 4.2.1.7. Other bioreceptors. Another promising bioreceptor elements are affibodies, a new class of engineered proteins which have a considerable affinity and specificity to various targets, proteins or peptides. As well as antibodies, affibodies are affinity proteins but with improved properties such as a robust spatially defined structure [79,102]. We may also mention phage peptides [103], which are receptor binding proteins localized on the phage tail and responsible for bacterial recognition. However, all these new bioreceptors are still in an early stage of study and development of operative biosensors

is another challenge for the scientific community for the following years. 4.2.2. Detection of bacterial components Impedimetric transducers based on interdigitated electrodes may be alternatively used for detection of bacterial contaminants. Gram-positive and gram-negative bacteria are producers of toxins that are hazard to human health as they are potential inducers of sepsis, an uncontrolled inflammatory response by the host cells that may result in multi organ failure and death [104,105]. One type of toxins are endotoxins, also known as lipopolysaccharides (LPS), that are ubiquitous markers and the major structural component of external membrane of gram-negative bacteria [106]. Other highly potent toxins are exotoxins, which are produced inside the bacteria cells and may be secreted or released during bacteria disruption. Exotoxins are classified depending on their mode of action [107]. Several lethal exotoxins including Shiga toxin, cholera toxin or anthrax are produced by different bacterial strains. For selective detection of endotoxins concanavalin A may be used as a biorecognition element. An impedimetric transducer based on a three-dimensional IDEA with immobilized Con A has been recently reported by Brosel-Oliu et al. [108]. In this case layerby-layer method was used to immobilize Con A over initial polyethyleneimine (PEI). The developed biosensor was demonstrated to be able to detect bacterial LPS in a very short detection time (20 min) with a limit of detection of 2 mg/mL. An impedimetric immunosensor with a flow-injection system for label-free detection of cholera toxin was reported [109]. The antibodies were immobilized on gold interdigitated electrodes to monitor the changes in the charge transfer resistance depending on the toxin concentration. The authors reported the possibility to detect really low concentrations of 1 ng/mL of cholera toxins. Table 2 presents the list of recent publications on application of interdigitated electrodes with different biorecognition elements for the detection of bacteria and bacterial contaminants. 4.2.3. Indirect and non-selective bacteria detection To prevent the matrix effect of complex samples on an IDEA response they can be used for indirect measurements. In this case, in order to carry out the specific detection of bacteria, one possibility is to capture them on micro or nanoparticles functionalized with specific bioreceptors, usually magnetic beads coated with affinity biomolecules (antibodies [123], aptamers [124] or lectins [125]). Afterwards the solution with bacteria concentrate may be transferred to the sensor surface to perform the impedance measurements. The use of micro/nanoscale magnetic beads presents several advantages in reference to the interaction with bacteria. Due to their high surface-volume ratio and small size a higher density of immobilized bioreceptors may be achieved resulting in a higher efficiency of the bacteria capture. In addition, nanoparticles can be used to concentrate bacteria in complex samples with low concentrations, reducing the noise produced by the unspecific targets [20]. Another advantage is that it is possible to use the electrodes multiple times because no biorecognition elements are directly immobilized on the surface. Several studies have been performed that use microbeads or nanoparticles coated with different biorecognition elements to capture target bacteria cells. The most cited works in this field were published by Varshney and co-workers [126,127]. Varshney et al. [126] developed a label-free biosensor based on a gold IDEA coupled with magnetic nanoparticles biofunctionalized with antibodies for the detection of E. coli O157:H7 in food samples. Magnetic nanoparticles were functionalized previously with streptavidin to immobilize biotin-labelled polyclonal anti-E. coli

Please cite this article as: S. Brosel-Oliu et al., Impedimetric transducers based on interdigitated electrode arrays for bacterial detection e A review, Analytica Chimica Acta, https://doi.org/10.1016/j.aca.2019.09.026

S. Brosel-Oliu et al. / Analytica Chimica Acta xxx (xxxx) xxx

antibodies to carry out selective pre-concentration of bacteria. Afterwards the nanoparticles were transferred into solution with low electrolyte conductivity and the sample was spread over the IDEA surface. This method showed the limit of detection of 7.4$104 CFU/ mL and 8$105 CFU/mL in pure cultures and food samples, respectively, with a total detection time of 35 min. The same strategy was employed lately by Varshney et al. [127] with a micro-fabricated flow cell to detect the same bacterial strain. In this case, the detection limit was as low as 1.6$102 and 1.3$103 cells in pure cultures and ground beef samples, respectively, corresponding to 4.2$104 CFU/mL. Other platforms were developed by Kanayeva et al., 2012 [128], combining immunomagnetic nanoparticles and an integrated microfluidic chip with a gold interdigitated electrode to detect Listeria monocytogenes. More recently, a novel strategy was presented by Xu and collaborators [129]. They reported the use of magnetic beads functionalized with antibodies to capture E. coli O157:H7 and Salmonella typhimurium bacteria. After the capture of target bacteria, the sample was treated with specific antibodies labelled with glucose oxidase, forming a sandwich magnetic beadsantibody-bacteria and transferred to a glucose solution of low ion strength. The enzymatic reaction produced gluconic acid and the increase in solution conductivity was registered by impedance measurements with a screen-printed interdigitated gold microelectrode. This system demonstrated the possibility to detect both types of bacteria in the range of 102e106 CFU/mL in pure culture samples, and the LOD of 2.05$103 CFU/g and 1.04$103 CFU/mL, for E. coli in ground beef samples and Salmonella in chicken rinse water, respectively. Despite low detection limit and the possibility to reuse this sensor, the reported system has limited practical application as additional labelling steps are required. Some studies using interdigitated electrodes combined with micro/nanoparticles are presented in Table 3. However, in the majority of publications devoted to application of micro and nanoparticles for bacteria detection, the optimal size or chemical nature of these particles is poorly studied [69,125], and varies depending on the kind of transducer or the sample under analysis. Moreover, increased number of the detection process steps, from the initial sample treatment to the final bacteria detection, may result in the loss of sensitivity and reproducibility in the final biosensing system. Another possibility to facilitate the capture of bacterial cells on the sensor surface may be achieved by combination of impedimetric transducers and dielectrophoresis (DEP), usually combined in microfluidic or lab-on-a-chip devices. Basically, DEP forces provoke the motion of particles due to their polarization in the presence of non-uniform electric fields [130]. Bacterial cells possess charged components which enables their polarization in the presence of an electric field without generation of excessive heating or electrochemical effects. These properties are not limited to bacteria, also other cells, yeast or viruses, as well as biomolecules like DNA or proteins may be exposed to DEP. Since IDEA design is based on a periodic electrode structure they can be employed to generate DEP forces. The electric properties of bacteria can be taken in advantage to move bacterial particles depending on the dielectrophoretic forces employed. For example, positive dielectrophoretic forces enable to trap bacteria on the edges of electrodes (that corresponds to high electric field regions), while in the case of negative dielectrophoresis bacteria are pushed away from the electrode surface [14]. However, the motion of bacteria will depend on the frequency, the applied potential or the viability of bacterial cells. First works of using DEP and impedimetric transducers for bacteria concentration and detection were reported by Suehiro and co-workers [40], defining the combination of both techniques as

13

dielectrophoretic impedance measurements (DEPIM). Suehiro et al. [36] also proposed a method to improve the sensor selectivity by immobilizing antibody molecules on a chip surface in advance of E. coli bacteria trapping by positive DEP. Similar approach was used by Yang et al. [131] for the concentration and specific capture of Listeria monocytogenes by employing DEP and IDEA with immobilized anti-Listeria antibodies. Publications on dielectrophoresis and impedance measurements for detection of bacteria have been s et al. [132] and Fernandez extensively reviewed by Paez-Avile [133]. Here, we summarized some of the published works using the DEP in combination with IDEA (see Table 3). The main advantage of the DEP separation technique is the possibility to concentrate bacteria in the cases when they are at really low concentrations, improving the attraction of these microorganisms towards the electrode sensing surface. Additionally, the DEP based impedance detection requires almost no sample preparation step and is rapid and easy-to-use [14]. However, one of the main limitations of this method is that the DEP forces depend on the conductivity and composition of the supporting solution, reducing its utility for in situ applications in complex samples. IDEA based impedimetric transducers may be regarded as a powerful tool for monitoring bacteria attachment to solid surfaces and biofilm formation, especially in their early development stage [134,135]. The major interest in biofilm detection relies on the fact that the biofilm can exhibit resistance to antimicrobial agents, like antibiotics, causing several problems in industrial environments and healthcare [136]. The impedance measurements showed that bacterial cells attachment to IDEA sensors provoke capacitance and resistance changes [137]. Kim et al., 2012 [134] presented a rapid impedimetric system for detection of Pseudomonas aeruginosa. Paredes et al. reported various systems for the biofilm growth control [138e140], although all the studies were performed in optimal conditions and no real applicability was demonstrated. In Settu et al. [141] focus their study on the detection of E. coli biofilms formation in urine samples, one of the main bacteria producing urinary tract infections [142]. The detailed information on biofilm monitoring using IDEA devices is summarized in Table 3. In the case of biofilm monitoring using impedimetric transducers, the majority of reported works register impedance changes in long period times, corresponding to assembling of cells and formation of mature biofilms. Nevertheless, a relevant aspect to be taken into account is the importance of the initial stage of a biofilm formation that should be detected in short time to prevent the derived problems mentioned earlier. Taking into consideration rather small impedance changes produced by this process a special attention should be given to the experiment planning and reproducibility of the results. In addition, impedance technique as a tool for monitoring the changes on the electrode surface may be limited due to the complexity of the biochemical and metabolic processes during the biofilm growth and, also, due to possible presence of other compounds that may adsorb on the sensor surface and thus affect the impedance of the system under study. Therefore, to exclude possible problems associated with the drift of a sensor signal it is important to perform blank experiments in a supporting solution in the absence of analyte. Also, experiments in test samples should be performed in triplicate to guarantee statistical significance of the measured response. 4.3. Microbial based-biosensors Microbial biosensors integrate microorganisms as the biorecognition elements with a transducer to generate a signal proportional to the concentration of an analyte [153]. In the recent years microbial-based biosensors have been employed for detection of different targets in environmental, food and biomedical

Please cite this article as: S. Brosel-Oliu et al., Impedimetric transducers based on interdigitated electrode arrays for bacterial detection e A review, Analytica Chimica Acta, https://doi.org/10.1016/j.aca.2019.09.026

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Target bacteria

Biorecogni-ion element

IDEA material

Application

Detection time

Limit of detection (range of application)

Supporting solution/medium

Reference

Use of micro-nanoparticles E. coli O157:H7

Magnetic nanoparticles with antibody conjugates

Gold on silicon dioxide

35 min

7.4  104 CFU/mL (7.4  104 to 7.4  107)

Mannitol solution

[126]

E. coli O157:H7

Magnetic nanoparticles with antibody conjugates

Gold on silicon dioxide

35 min

1.6  102 cells (4.2  104 CFU/mL

Mannitol solution

[127]

Listeria monocytogenes

Magnetic nanoparticles with antibody conjugates

e

3h

[128]

Gold on ceramic substrate

e

Redox probe [Fe(CN)6]3-/4-) in PBS HEPES buffer

[143]

Salmonella enterica serovar (Salmonella typhi) E. coli

Antibody-coated magnetic nanobeads Antibody-coated gold nanoparticles AMPs

103 CFU/mL and 104 e105 CFU/mL in food samples. (103e107 CFU/mL) 104.45 CFU/mL (104 e107 CFU/mL) 102 CFU/mL

Mannitol solution

E. coli O157:H7

Detection of bacterial cells in food samples (ground beef) Detection of bacterial cells in food samples (ground beef) Detection of bacterial cells in food samples (lettuce, milk, and ground beef) Detection of bacteria

25 min

1 CFU/mL (1e106)

E. coli K12

e

10 min

e

Dielectrophoresis (DEP)

Biofims monitoring

E. coli K12

Antibodies

Listeria monocytogenes

Antibodies

Staphylococcus epidermidis

e

E. coli O157:H7

Antibodies

Salmonella

Antibodies

E. coli O157:H7 and Salmonella typhimurium Pseudomonas aeruginosa PAO1 Different Staphylococcus strains Staphylococcus epidermidis Escherichia coli

Antibodies

e

Detection of bacteria in clinic samples Golds on PET (Polyethylene Detection of bacteria in terephthalate) food samples Crome on glass substrate Evaluate vaiable and non-vaible cells Crome on glass substrate Concentration and detection of bacteria Platinum on silicon dioxide Concentration and detection of bacteria Aluminium on silicon Bacteria sensing dioxide Gold on glass Concentration and detection of bacteria Gold on glass Concentration and detection of bacteria Gold on glass Concentration and detection of bacteria Gold on silicon dioxide Biofilm formation monitoring Gold on silicon dioxide Biofilm growth monitoring

e e

Gold on silicon dioxide Gold on silicon dioxide

Pseudomonas aeruginosa

e

E. coli K12

e

Gold on a PCB (printed circuit board) Gold on glass

e

E.coli JM109 and Salmonella e (ATCC 14028)

Platinum on glass

Gold on silicon dioxide

z1 h

[144]

e

10 CFU/mL

e

e

Potable water and apple juice 0.1 M mannitol solution 0.1 M mannitol solution DI water

20 min

105 CFU/mL

Dilluted PBS

[146]

39 CFU/m

DI water

[147]

40 min

7 cells/mL

Poultry products

[148]

1h

10 cells/mL

Raw chicken products [149]

z1 h

e

M9 culture medium

[134]

16e30 h

e

TSB culture medium

[138]

TSB culture medium Urine

[139] [141]

TSB culture medium

[150]

LB medium

[151]

LB culture medium

[152]

4

Biofilm growth monitoring 10 h e Growth of bacteria in urine 12 h 7  100 to 7  108 cells/ml samples Biofilm growth monitoring 18 h e (168 h total) Biofilm formation 24 h e monitoring and treatment Biofilm formation 48 h e monitoring

[145] [40] [36] [131]

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Please cite this article as: S. Brosel-Oliu et al., Impedimetric transducers based on interdigitated electrode arrays for bacterial detection e A review, Analytica Chimica Acta, https://doi.org/10.1016/j.aca.2019.09.026

Table 3 Applications of interdigitated electrodes: detection of bacteria using micro/nanoparticles; IDEA combined with dielectrophoresis technique; monitoring of a biofilm formation.

S. Brosel-Oliu et al. / Analytica Chimica Acta xxx (xxxx) xxx

applications. In the development of microbial biosensors several important aspects should be considered [154], mainly bacteria immobilization on a transducer and viability of microorganisms. The majority of reported microbial biosensors rely on information associated with the metabolic activity of bacteria. For example, the measurement of the respiratory activity can be correlated with the biological oxygen demand (BOD) or metabolic activity related with consumed nutrients [153]. In those cases, bacteria have to remain alive on a transducer surface to produce a measurable response. Other common applications of microbial biosensors are the monitoring of toxic compounds (heavy metal ions, organophosphorus pesticides, phenols and cyanides) in the environment, fermentation processes control, detection of antibiotics or toxins residues in food industry, or detection of hormones and glucose in clinical diagnosis [155]. Only a few works on application of microbial biosensors based on interdigitated electrodes as impedimetric transducers have been reported. Hnanien and coworkers [156] developed a bacterial impedimetric biosensor for detection of trichloroethylene, a common organic pollutant. Here Pseudomonas putida strain was immobilized on gold interdigitated microelectrodes functionalized with carbon nanotubes grafted with anti-Pseudomonans antibodies. The reported biosensor presented a limit of detection of 20 mg/mL and a linear response up to 150 mg/mL. Moreover, natural water samples spiked with trichloroethylene were successfully tested demonstrating the applicability of the proposed biosensor. Brosel-Oliu et al. [157] reported the development of a microbial biosensor for monitoring the bacteria response to antibiotics. In this work, 3D interdigitated electrode array (3D-IDEA), in which the electrode digits are separated by insulating barriers, have been employed as impedimetric transducer and E. coli bacteria as the biosensing element. Here a novel strategy was employed to selectively immobilize and concentrate bacteria in the spaces between the barriers to improve the reproducibility in the E. coli immobilization and to increase the sensitivity for monitoring bacterial response to antibiotics. The authors demonstrated the possibility to register the effect of ampicillin on E. coli by means of impedance changes in a short detection time of 1e2 h, really fast compared with standard antibacterial susceptibility test methods [158]. The main inconvenient of microbial biosensors is that they typically suffer from poor selectivity to a single target analyte due to non-specific cellular response to various substrates. However, with the development of biotechnology bacteria and other microorganisms can be genetically engineered with specific metabolic pathways and their selectivity to specific targets can be enhanced [159e161]. 5. Conclusions The importance of impedance spectroscopy technique for bacteria detection has increased significantly during last decades due to advantages of interdigitated electrode arrays, that offer low-cost and easy-to-use impedimetric transducers for bacteria growth monitoring and specific detection of bacteria. The large number of publications focused on basic research and applications of these biosensors reflects the importance of this field. However, realworld practical applications of biosensors for bacteria detection are still limited. The main problems in this respect are: matrix effect of complex samples, such as food or biological fluids; high cost of biorecognition elements and their poor stability; problems with reproducibility of immobilization processes; absence of the regeneration methodology allowing to employ the sensor multiple times in order to reduce costs per assay; poor understanding of the effect of biochemical reactions on the measured impedance response. Therefore, it is important to focus the efforts on solving

15

these limitations to implement real practical applications with these sensors. It should be noted that the abovementioned problems are not specific to impedance spectroscopy. Other techniques, like surface plasmon resonance (SPR) or surface enhanced Raman scattering (SERS), that rely on surface interaction of a biorecognition element with an analyte, suffer from them. There are many high quality papers that put much attention to the interpretation of experimental impedance spectra. However, in general, papers on impedance studies of bacteria sensors lack the information regarding association of the equivalent electrical circuit components with processes occurring on the sensor surface. Without thorough insight into the mechanism of sensors response and its effects on the impedance it will not be possible to optimize the sensor parameters and measurement protocols to enhance selectivity, sensitivity, detection limit and stability. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. CRediT authorship contribution statement Sergi Brosel-Oliu: Investigation, Data curation, Formal analysis, Writing - original draft. Natalia Abramova: Methodology, Formal analysis, Supervision, Writing - review & editing. Naroa Uria: Methodology, Investigation, Writing - original draft. Andrey Bratov: Conceptualization, Supervision, Writing - original draft, Writing - review & editing. Acknowledgements The authors acknowledge financial support from the Spanish Ministry of Economy and Competitiveness (project PCIN-2017-031) and S.B.O fellowship (BES-2015-071250). References [1] L.C. Clark, C. Lyons, Electrode systems for continuous monitoring in cardiovascular surgery, Ann. NY Acad. Sci. 102 (1962) 29e45. [2] D.M. Shin, J.R. Choi, J.W. Oh, H.K. Kim, D.W. Han, K. Kim, Y.H. Hwang, Exploring the use of impedance spectroscopy in relaxation and electrochemical studies, Appl. Spectrosc. Rev. 53 (2018) 157e176. [3] G. Lillie, P. Payne, P. Vadgama, Electrochemical impedance spectroscopy as a platform for reagentless bioaffinity sensing, Sens. Actuators B Chem. 78 (2001) 249e256. [4] E. Katz, I. Willner, Probing biomolecular interactions at conductive and semiconductive surfaces by impedance spectroscopy: routes to impedimetric immunosensors, DNA-Sensors, and enzyme biosensors, Electroanalysis 15 (2003) 913e947. [5] J.S. Daniels, N. Pourmand, Label-free impedance biosensors: opportunities and challenges, Electroanalysis 19 (2007) 1239e1257. [6] A. Bratov, S. Brosel-Oliu, N. Abramova, Label-free impedimetric biosensing € ning, A. Poghossian (Eds.), using 3D interdigitated electrodes, in: M.J. Scho Label-Free Biosensing: Advanced Materials, Devices and Applications, Springer International Publishing, Cham, 2018, pp. 179e198. [7] C. Berggren, B. Bjarnason, G. Johansson, Capacitive biosensors, Electroanalysis 13 (2001) 173e180. [8] S.M. Radke, E.C. Alocilja, Design and fabrication of a microimpedance biosensor for bacterial detection, IEEE Sens. J. 4 (2004) 434e440. [9] L. Yang, Y. Li, G.F. Erf, Interdigitated array microelectrode-based electrochemical impedance immunosensor for detection of Escherichia coli O157: H7, Anal. Chem. 76 (2004) 1107e1113. [10] H.H. Nguyen, S.H. Lee, U.J. Lee, C.D. Fermin, M. Kim, Immobilized enzymes in biosensor applications, Materials 12 (2019) 1e34. [11] L. Yang, R. Bashir, Electrical/electrochemical impedance for rapid detection of foodborne pathogenic bacteria, Biotechnol. Adv. 26 (2008) 135e150. [12] P. Kenchetty P, T. Miura, S. Uno, Computer simulation for electrochemical impedance of a living cell adhered on the inter-digitated electrode sensors, Jpn. J. Appl. Phys. 58 (SB) (2019) SBBG15. [13] M. Riedel, F. Lisdat, Biosensorial application of impedance spectroscopy with €ning, A. Poghossian (Eds.), Label-Free focus on DNA detection, in: M.J. Scho

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Dr. Sergi Brosel-Oliu obtained a BSc in Biology (2012) and a MSc in Applied Microbiology (2013) in the Autonomous University of Barcelona. He has recently obtained his PhD degree at the same university with the thesis entitled: “Interdigitated electrode arrays (IDEA) impedimetric transducers for bacterial biosensing applications”. Currently he is a post-doctoral researcher at the BioMEMS group of the Microelectronics Institute of Barcelona (IMBCNM, CSIC) working on the development of novel devices for biosensing applications.

Natalia Abramova received her MSc degree in analytical chemistry from St. Petersburg (Leningrad) State University in 1984 and started working as a research chemist in the Chemical Institute of Leningrad University. In 1991 she received her MSc degree in solid state chemistry and in 1998 her PhD degree in analytical chemistry from the same University. Since then she has been working at the nica de Barcelona, Centro NacioInstituto de Microelectro  nica (IMB-CNM), CSIC in Barcelona, nal de Microelectro Spain. Her scientific interests are research, development and analytical applications of microelectronic chemical sensors.

 obtained her degree in Biology from the Naroa Uria Molto University of the Basque Country and PhD in Microbiology from the Autonomous University of Barcelona (2012). She completed her thesis entitled "Microbial Fuel Cell performance: design, operation and biological factors" in the Laboratory of Environmental Microbiology. The research carried out was based on the development of sensors for the detection of microbial activity through the use of microbial fuel cells. She is currently a post-doctoral researcher at the BioMEMS group of the Microelectronics Institute of Barcelona (IMB-CNM, CSIC), where she works on the development of new technologies for the detection, quantification and control of biological components.

Please cite this article as: S. Brosel-Oliu et al., Impedimetric transducers based on interdigitated electrode arrays for bacterial detection e A review, Analytica Chimica Acta, https://doi.org/10.1016/j.aca.2019.09.026

S. Brosel-Oliu et al. / Analytica Chimica Acta xxx (xxxx) xxx Andrey Bratov received his Ph.D. in chemistry in 1987 from the Chemistry Department of the Leningrad (now St.Petersburg) State University. Till 1993 he worked as a senior researcher in the Laboratory of Chemical Sensors of the St.Petersburg University working on the development of ISFET-based sensors. In 1993-1995 he was invited as a Visiting Professor to the Sensors and Biosensors Group

19 of the Autonomous University of Barcelona. From 1995 he works at the Institute of Microelectronics of Barcelona, currently being a senior researcher of the BioMEMS Group. His main research activities are concentrated on application of microelectronic technology to chemical and biochemical sensors development.

Please cite this article as: S. Brosel-Oliu et al., Impedimetric transducers based on interdigitated electrode arrays for bacterial detection e A review, Analytica Chimica Acta, https://doi.org/10.1016/j.aca.2019.09.026