AC Electrokinetics-Enhanced Capacitive Virus Detection
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The occurrence and spread of various serious viral outbreaks in pandemic dimension is one of the few major threats to public health and life worldwide nowadays. A disease diagnosis method that is sufficiently sensitive, rapid, and compact for point-of-care (POC) detection, and requires minimal sample pretreatment is highly desired. Hence, developing such a detection method for POC detection of viral disease is of the utmost significance for medical healthcare. Among different types of biosensors, capacitive biosensors, which fall into the category of electroanalytical biosensors, stand out and have shown great success due to their excellent performances and high potential to be developed as easy-to-handle devices. Capacitive sensors reported for virus detection are a type of surface-based affinity sensors. Specific binding reactions occurring on the sensor surface will cause changes in the dielectric properties or thickness of the interfacial layer at the electrolyte-electrode interface. By measuring the sensor’s capacitance, the sensor can convert the quantity of target analytes, such as antigen, or nucleic acids from virus, or antibody from patient serum, into readable outputs.
This chapter firstly provides some background information on the significance of capacitive virus detection and briefly reviews the current status that scientists and researchers have accomplished in developing POC tests of viral disease (section “Introduction”). Section “Capacitive Biosensors” briefly presents various receptors that can be utilized and the sensing mechanism. Section “AC Electrokinetic (ACEK) Enrichment” introduces alternating current electrokinetic (ACEK) effects that can be incorporated into capacitive sensing. Last, sections “Sensor Designs” and “Sensor Performances” present sensor electrode characterization and sensor performances, respectively. Sensor characterization methods include equivalent circuit extraction and fitting with respect to the electrode cell’s impedance spectrum, electrodes surface treatment, and data acquisition and analysis. The discussion of sensor performance includes the optimization of buffer solutions, electrical signals, and sensor specificity, sensitivities, etc.
KeywordsCapacitive biosensor AC electrokinetic Point-of-care Influenza A Human herpesvirus-1 Zika virus Virus Nucleic acids
Expansion of human activities and process of globalization speed up the pace of people’s life and interactions, as well as the spread of pathogens. Recent years have witnessed several serious viral outbreaks such as H5N1 bird flu, Zika virus, and Ebola virus. These recent outbreaks rapidly spread around the world to become pandemics with devastating effects on populations. An on-site screening tool for viral infections will be very helpful to control the spread of such viral outbreaks. Nowadays, biochemical diagnostics is either performed using sophisticated, expensive laboratory equipment capable of accurate measurement of complex biological interactions and constitutes, or by easy-to-handle, portable device for use by nonspecialists for decentralized, on site, or home analysis. The former are expensive and the latter are mass produced and inexpensive, and often referred to as biosensors. The best-known biosensor is glucose sensor. Professor Clark has been considered as the “father of biosensors” and the modern-day glucose sensor used daily by millions of diabetic patients is based on his research. The field of biosensor has attracted a great amount of research and development efforts since Professor Leland C. Clark’s monumental paper on the development of the first enzyme glucose oxidase biosensor in 1962 (Clark and Lyons 1963). Researchers and scientists from the fields of chemistry, physics, microbiology, and various disciplines of engineering have been deeply involved in this interdisciplinary field. There have been remarkable development and progress of sophisticated and accurate traditional laboratory-based biodetection instruments in the last three decades.
For virus detection and quantification, traditional and the most commonly used methods as of now include measurements of viral infectivity (such as viral plague assay), detection of viral proteins and nucleic acid (such as immunoblotting), and direct counting of virions (such as viral flow cytometry and transmission electron microscopy) (Pankaj 2013). For biosensors, based on the sensing targets, virus detection can be achieved by detecting the nucleic acid extracted from virions or detecting the virions themselves. For example, polymerase chain reaction (PCR) is one of the most widely used laboratory methods for detection of viral nucleic acids. This method is able to determine viral DNA inside virions. For RNA virus, such as Zika viruses, by converting RNA into DNA at the very first step, PCR can also be used to determine viral RNA. This method is known as reverse transcriptase PCR (RT-PCR). PCR has excellent sensitivity and specificity. However, this method needs several hours to yield results, with moderate requirements on sample treatment, facilities, and cost. An alternative category of sensing methods with less cost are immunoassays, which is based on highly specific antibody-antigen interaction, including immunoblotting (also known as western blot), immunoprecipitation (IP), enzyme-linked immunosorbent assays (ELISA), etc. Among them, ELISA is one of the most common test formats used for laboratory diagnosis of infections (Lequin 2005). Indirect detection of viral infection is often adopted, for example, through specific detection of antibodies in body fluids that are produced as a part of immune response, with the antigen of causative agent as a specific probe. Comparing with PCR, ELISA is not as sensitive as PCR, but the assay cost is much lower.
While being effective, the above traditional laboratory-based sensing methods for virus detection are limited by sample enrichment and purification required prior to analysis, expense, and time. These methods are not compatible with point-of-care (POC) settings due to their turnaround time, expenses, and labor-intensive sample preparation and handling process. Under the circumstances of serious viral outbreaks, a POC diagnostic device is desired that should be rapid, low-cost, sensitive, specific, and reproducible, with minimum need for sample preparation, compared to established traditional techniques.
Performances of sensors for viral sequences and specific antibodies
Wang et al. (2017)
Samanman et al. (2011)
Virus antibodies (ZIKA)
Afsahi et al. (2018)
Virus antibodies (ZIKA)
10 antibody molecules/30 μL
Wang et al. (2019)
While considerable research effort has been devoted to developing such biosensors, there are few successful POC devices being routinely used in real diagnostic applications at the bedside or in the clinic. POC diagnostic systems require the following critical attributes, namely sufficient sensitivity, robustness, simple test procedure, and short sample-to-result time. The obstacle to achieving rapid detection is the long diffusion time for the target bioparticles to reach the sensing site of a sensor. So accelerating the diffusion process has been an essential part of recently microfluidic study. Most of the reported biomolecular sensors work with heavily processed samples, requiring purification, pre-concentration, etc. in addition to sophisticated data processing and expensive equipment. Another challenge is specificity. A number of ultrasensitive affinity sensing methods have been developed, many based on nanotechnology. However, very few of the newer ultrasensitive methods have been evaluated with real patient samples, which is a key to establishing clinical sensitivity and selectivity.
Capacitive sensors for direct virus detection can be divided into two main categories: immunosensors that detect the virions (Fig. 2a), and nucleic acid sensors that detect specific nucleic acid sequences (Fig. 2b) extracted from virions. The immunosensors in Table 1 are developed for the detection of specific antibody in serum, while here the immunosensors are for the detection of virions using specific antibody as the probe, as shown in Fig. 2a. Immunosensors for label-free measurements of various analyte have been studied and developed for many reasons. Among various detection schemes, such as optical, mass-sensitive, and electrochemical detection (Wang et al. 2017; Samanman et al. 2011; Cheng et al. 2017a), electrical immunosensors are expected to have better detection limits and less complicated instrumentation. This makes electrical immunosensors a good candidate for POC detection of targets such as virions. The same can be said for electrical nucleic acid sensors.
Nucleic acid (DNA or RNA) sensors utilize oligonucleotide primers such as human herpesvirus-1, or HSV-1, DNA probes shown in Fig. 2b as receptors in biosensing. They are short artificially synthesized nuclei sequences with high specificity. Once they reach the sensor electrodes surface, single strand target DNA (i.e., HSV-1 DNA) will hybridize with the immobilized HSV-1 DNA probes. Such reactions need to be sensed and transduced into singles that can be recorded and further quantitatively analyzed.
Currently, all nucleic acid biosensors suffer from lack of sensitivity to be used directly for pathogen detection. As a result, nucleic acid biosensors are often used after target amplification such as PCR or labeling by nanoparticles, molecular beacons to amplify the signal, and/or by incorporating an enrichment scheme such as electrophoretic preconcentration or magnetic beads for the target to reach detectable level. However, labeling requires multistep process, complicated preparation of functionalized beads, and oftentimes, careful design of receptor probes. Moreover, it should be noted that almost all the reported work was based on detecting ssDNA oligonucleotides or short DNA segments (20–300 bps) as targets. The reasons could be that shorter DNA has a higher diffusivity than longer DNA that improves hybridization rate, and amplicons from PCR process are fragmented DNA and most DNA sensors are developed to detect PCR products. As extra and further steps in sample processing are needed to release and obtain the desired short DNA segments from virus, the use of DNA sensors still faces great challenges in achieving point-of-care detection of clinical samples.
As with all surface-based biosensors, it is very important to design the sensor surface and assay protocols in such a way that it can ensure significantly higher specific binding reactions than nonspecific ones. As a result, for electrical sensors, especially capacitive biosensors, the immobilization of bioreceptors layer becomes very critical. Usually, a blocking reagent, illustrated as gray spheres in Fig. 2, is used to cover the bare part of electrodes surface. If the sensor surface is not completely covered and blocked, the open space can allow any analyte particles to deposit and cause false positive readings. Nevertheless, nonspecific binding is still challenging which makes it difficult to differentiate false positives from true positives when testing complex samples.
Capacitive Sensing Mechanism
Generally, a decrease in Cint due to receptor-target binding (e.g. antigen–antibody binding or DNA-DNA probe hybridization) is commonly observed. In a diluted buffer solution, the EDL is relatively thick. As EDL envelops the antibodies on the electrodes, fine features on the scale of EDL thickness will be lost, and the Cint change will be dominated by an increase in its thickness, that is, Cint reduces. When EDL thickness is comparable to that of antibody topology, a positive change of Cint is possible, especially in a buffer solution of high ionic strength. Either an increase or a decrease in Cint can possibly result from antigen–antibody binding and DNA-DNA probe hybridization. As a matter of fact, an increase in Cint was consistently observed in influenza A virus detection (Cheng et al. 2017a, b) and HSV DNA detection (Cheng et al. 2017b), while a decrease in ZIKA virus RNA detection (Cheng et al. 2017c).
AC Electrokinetic (ACEK) Enrichment
Therefore, ACEK effects can occur when an inhomogeneous AC electric field is applied through microelectrodes to sample solution (Wu 2008a). Directed particle movement can be caused by DEP, and particle can also be carried by microflows such as ACEO or ACET flows (Cui et al. 2016) to reach the microelectrodes. For virus detection in biological matrix, aided by ACET, positive DEP (pDEP) dominates and is used for bioparticle enrichment around electrodes to accelerate the biological reactions between probe and target. ACEO is negligible due to the high conductivity of the biological matrix. In addition, as biological reactions between probes and target molecules happen, the interfacial capacitance (Cint) change caused by the binding process is measured by the same applied ACEK signal.
Equivalent Circuit Fitting of the Electrode Sensor in Sample Solution
It can be concluded that Cint and Rs dominate the impedance response for the frequency at 100 kHz. Therefore, the extracted equivalent circuit can be simplified to a series connection of Cint and Rs. Consequently, the measured capacitance at 100 kHz can be directly used to indicate the reaction occurred on the electrode surface, which greatly simplifies the process of interpreting experimental data.
Electrodes Surface Treatments
However, in most cases this hydrophobic character is not desirable for sensors, especially for detection in an aquatic medium. Plasma treatment is a good method for increasing the surface hydrophilicity by creating OH dangling bonds and enriching O− ions on the surface without influencing the electrode microstructure characteristics. After 10 min of vacuum plasma treatment (PLASMA ETCH PE-50), the water drop completely infiltrates into the electrode surface (Fig. 6c), indicating a marked surface transition from hydrophobicity to hydrophilicity. The immobilization efficiency of sensors treated with plasma is improved since more bioreceptors attached to the electrode surface made the surface less likely to become saturated. Besides plasma treatment, ozone treatment can also improve the hydrophilicity of the electrode surface by enriching O− ions on the surface.
Measurements and Data Analysis
In ACEK capacitive sensing, Cint can effectively detect molecular deposition on the electrode surface with high sensitivity and specificity in a much quicker manner. Cint is found by measuring the sensor cell’s impedance at a fixed AC frequency and voltage continuously during the testing. The interfacial capacitance of the electrodes is sampled and recorded periodically by an Agilent 4294A impedance analyzer for 20 s.
Sensor Performance with Analytical Samples
Assays with Various Functionalization and Hybridization Buffers
Consideration for buffers selection includes whether the buffers will be suitable for electrodes surface functionalization, probe-target binding reaction, and the induction of ACEK effect during assay. In general, functionalization buffer plays a vital role in sensor performances such as the reliability and repeatability. This is because functionalization buffer with high ionic strength can screen the electrical charges of nucleic acids. Therefore, during probe immobilization process, using buffer with higher ionic strength can possibly reach higher coverage of probes on the electrode surface. However, nucleic acids will coil up if the functionalizing buffer contains too many ions, losing the ability to bind with other molecules. As for hybridization buffers, a lower ionic strength helps to linearize the target nucleic acids and expose the binding region. Additionally, due to its weaker electrostatic screening, nonspecific binding can also be reduced. Hence, ionic strength of the hybridization buffer and its electrostatic screening would significantly affect sensor’s sensitivity and specificity. These conclusions can be illustrated by the process of buffer selection for HSV-1 DNA detection.
Based on the given results in Fig. 9, HSV-1 probe in 0.05 × PBS and HSV-1 DNA (target), HSV-2 (interference) in 0.5 × SSC are considered to be optimal with responses of −3.90 ± 0.52%/min (9 pg/mL), −6.92 ± 0.94%/min (90 pg/mL), and −9.72 ± 0.63%/min (900 pg/mL). The sensor’s LOD is defined as 3 standard deviations from the response of the background control (−0.22 ± 0.30%/min), so the cut-off d|C|/dt is calculated to be −1.12%/min, which corresponds to an HSV-1 DNA concentration of 0.986 pg/mL (6.38 copies/μL or 0.0106 fM). Tests of interference (HSV-2 DNA) also demonstrate a good specificity with a low response of −0.19 ± 0.60%/min at a concentration (5 ng/mL) 550 times higher than that of HSV-1.
Assays Under Various Applied AC Signal Frequency and Voltage
Next, AC voltages varying from 5 mV to 100 V are used to measure 1.52 ng/mL influenza A virus sample on functionalized electrodes. The background blank buffer, which is 0.1 × PBS-T, is also tested on the functionalized electrodes from 5 mV to 100 V as control. Negative control experiments with 152.5 ng/mL influenza A virus sample are measured under the same voltage conditions on dummy electrodes (electrodes without antibody). Experiments with each voltage are repeated three times.
Sensor Performance with Clinical Samples
Dilution Factor Optimization
It is common practice to dilute clinical samples in standard buffer. Due to the complexity of clinical samples, highly diluted samples can reduce nonspecific binding, which improves the selectivity of the sensor. With more dilution of clinical samples, chances of false positive results can be reduced. However, sensor’s sensitivity will also suffer since the concentration of target particles is reduced at the same time. The optimization dilution factor helps to decide which dilution can be used for the bind tests of unknown swab samples in the next step. In addition, clinical samples may contain background matrices that interfere with capacitance measurements.
Detection of influenza A Virions in Nasal Swab Samples
Blind tests for a panel of 20 nasal swab samples (10 positive, 10 negative) are conducted to detect influenza A virions. All samples are 1:100,000 diluted with 0.1× PBS-T. The threshold value is set at −0.40%/min, which is also the LOD from previous tests with spiked samples, meaning that samples with a response more negative than −0.40%/min will be considered as positive samples and others negative.
Detection of HSV-1 DNA in Serum Samples
Detection of Zika Virus RNA in Serum/Lysing Samples
Summary of the sensor performances
Influenza A virion
0.1 × PBS-T
gDNA/human herpesvirus 1
0.5 × SSC
0.5 × SSC
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