Open access peer-reviewed chapter

Application of Microfluidics in Biosensors

Written By

Jing Wang, Yong Ren and Bei Zhang

Submitted: November 26th, 2018 Reviewed: February 28th, 2020 Published: May 20th, 2020

DOI: 10.5772/intechopen.91929

Chapter metrics overview

927 Chapter Downloads

View Full Metrics

Abstract

This chapter reviews the up-to-date researches in the field of biosensors integrated with microfluidic techniques, most of which are publications within the last 5 years. The features of these biosensors, their applications, challenges, and possible future research interests in this field are also reviewed.

Keywords

  • microfluidics
  • biosensor
  • bioreceptor
  • lab-on-a-chip
  • bioaffinity
  • PDMS
  • μPAD
  • paper-based microfluidics
  • electrochemistry
  • optics
  • surface plasmon resonance
  • colorimetric
  • fluorescent
  • cell culture
  • food safety

1. Introduction

Biosensors are defined, by Tudos and Schasfoort [1], as “analytical devices comprised of a biological element (tissue, microorganism, organelle, cell receptor, enzyme, antibody) and a physicochemical transducer. Specific interaction between the target analyte and the biological material produces a physico-chemical change detected by the transducer. The transducer then yields an analog electronic signal proportional to the amount (concentration) of a specific analyte or group of analytes” [1]. The features of biosensors include the bio-recognition unit and the transduction mechanism from biological signals to measurable electronic signals, e.g., color, current, voltage, capacitance, light intensity, wavelength, and phase. Major parameters to assess the performances of biosensors include the following:

  • High sensitivity. The sensitivity of a biosensor is always the first and one of the most important parameters in assessing its performance. The efficiency in capturing analytes, the specific characterization of the analyte, the capability of converting biological signals into electronic signals (or the response of the system), and the systematic and environmental noises both determine the sensitivity of a biosensor.

  • High stability and repeatability. The stability of a biosensor refers to the capability of a biosensor in performing consistently and reliably under designated environments, and the stability of a biosensor is especially important when assessing portable or wearable biosensors that usually are applied in scenarios involving varied temperature, velocity, humidity, pressure, lighting conditions, etc. The repeatability of a biosensor mainly refers to the long-term performance of a biosensor under the same conditions and is usually tested regularly in commercial biosensors in order to recalibration.

  • Quick response or real-time analysis and diagnosis. Real-time analysis usually delivers more information than providing a final result, e.g., binding rate, reaction time, kinetics, and saturation conditions, which can serve for the analysis in the applications of biological and chemical reactions and drug analysis. Response time required to bind sufficient molecules upon the sensing surface is typically determined by diffusion, which can extend to hours and even to days to generate a signal above the background noise level. This applies fundamentally to all sensors that accumulate and concentrate target molecules onto a transducer, including fluorophore-tagged molecules in microarray spots, label-free optical biosensors, and impedance-based sensors [2].

  • Low consumption of sample volume. The samples for biosensors are usually with low volume due to the nature, e.g., tissue, antibody, and some biological samples are with low concentration or small molecular weight, and this enforces biosensors to perform with minimum sample consumption.

  • Ease of operation. The application of biosensors goes from laboratory-based research to commercially available devices for at-home use. The operation of biosensors should eliminate professional operation or understanding of the device, but simply involves collecting samples and reading results.

  • High throughput. Single-function biosensors are fading away from stage even with extremely low cost. Biosensors should be able to integrate all the good qualities mentioned in above bullet points together with the capability of multiple-tasking.

In traditional clinical healthcare, interests are in high-quality biosensor for the measurement of physiological indices. With the development in the requests of Internet of Things and self-service techniques, the interests and emphasis in healthcare transfers from clinical healthcare to family healthcare, e.g., long-term monitoring of chronic disease [3], disease prevention and early detection, reachable clinical services for remote districts, etc. Under the precondition of high quality, biosensors miniaturized as portable or wearable are emerging to meet the new trend of era, which promise a bright future in health management and digital health; researches on the biological and instrumental parts of point-of-care (POC) and lab-on-a-chip (LOC) techniques belong to this area. The potential applications of biosensors include real-time health monitoring, remotely synchronizing health data with medical personnel, patient management, POC disease diagnosis, big data statistics in health management, etc. [4]. Real-time health monitoring in domestic applications enables patients to monitor the health status by themselves at home without the assistance of professional personnel at minimum cost. Health data synchronized with medical personnel spares the patients from transporting and waiting for outpatient services, saving time and reducing medical expenses. Based on the collected health data, a potential service of clinical diagnosis is possible in an artificial intelligent health system in the near future [5]. Meanwhile, these new applications impose more requirements on the researches and developments of biosensors, as stated below.

  • Low cost. For at-home applications, lower cost of biosensors is vital, so there are emerging researches on adopting cheap materials, simplifying sensing systems and adopting smart phones in data processing, etc.

  • Noninvasive collection of samples. Biosensors for sensing human samples, noninvasive sensing, is preferable, especially for everyday or frequent measurements. Researches using human samples as saliva, tear, sweat, and urine are one of the hottest topics.

  • Miniaturization of the biosensing systems [4, 5], including sample pre-processing unit, sensing unit, data collection/processing system, and data displaying unit.

  • The design of integrated sensor chip. A sensor chip with multiple functions is preferable especially for sensing human samples.

Advertisement

2. Challenges in biosensing technologies

All the qualities mentioned above, which both researchers and industry are seeking for, raise multiple challenges, and we try to summarize and list below:

  • Specific binding. The recognition of analytes should be specific only to the analytes which is not affected by other chemicals, molecules, or cells. This is significantly more challenging when the sample components are complex and mixed with various kinds of molecules. For example, the detection of one specific antibody in human blood sample should eliminate the effects of all other antibodies, cells, electrolytes, etc., the detection reflects only the concentration of this antibody, and the detection of one specific heavy metal ion in a real polluted water sample should be able to distinguish the reaction induced by all other ions.

  • Non-specific binding, i.e., biofouling, in some cases significantly introduces signal noise, drift, or delay in biosensors [6]. The most common method to reduce non-specific binding is to completely wash the binding surface with buffer after the binding processing is finished; thus the weak binding induced by non-specific binding could be eliminated to the minimum extent.

  • Properties of bioreceptors, e.g., concentration and alignment. Plenty of papers [3, 7, 8, 9, 10] presented the protocols of surface activation, modification, and functionalization, but the protocols greatly depend on operation and environment. Even following exactly the same protocol, the coverage rate of bioreceptors and the repeatability of operation may vary a lot, due to the immobilization of multiple layers on the sensor surface, which usually involves linking layers for stable sensor surfaces like gold and silicon, so the surface treatment protocols should be tested before operating the binding events. So far quite limited number of papers presented theoretical and/or experimental analysis on the effect of bioreceptor alignment/orientation on the performance of biosensors. The linking layer molecules are usually randomly polarized and oriented, which can induce destructive interference and dramatically reduce the collective charge polarization [11], and this means that even the surface treatment protocols could be repeated and the alignment of bioreceptors is another parameter that will highly affect the outcomes of the binding events. The detection becomes less sensitive. Chu [12] proposed a method to homogenize the orientation of the chemical linker on nanowire-based field-effect sensor by applying an external voltage on a metal plate about 1 mm above the chip surface at certain frequency while grounding the back gate electrode; thus the molecular conformation can be maintained for hours or longer, and this method has been tested and proven by the detection of DNA hybridization reactions with poly-15 T ssDNA, showing that the alignment process promotes the sensitivity by 10-fold.

  • Design of biosensor assay matrix. The effects of specific and non-specific binding on signal was tested and analyzed by Schneider [13, 14], which proves that for all the binding events, proper design of the sensor assay should be optimized, especially when the sample components is complex, for example, proper reference binding sites should be included in order to eliminate non-specific binding from different components. But this in another way increased the requirement in both the imaging capability of the biosensor and the data processing capability. Meanwhile, the surface treatment, modification, and functionalization [4, 7, 9, 10, 15, 16] will be more complicated and need to be tested and verified, and the complexity in sensor surface properties (e.g., various refractive indices of bioreceptors) requests better system compatibility and responsivity.

  • Low concentration target molecule within a low-volume sample, i.e., extremely limited number of analytes available for detection. For the example, in the research of POC and LOC, 20–50 μL finger prick blood contains over 20,000 kinds of biomarkers of clinical interest at concentrations as low as 10 pg./mL, meaning that only 106–107 available biomolecules for one target [2].

Advertisement

3. What is microfluidics?

The definition of microfluidics, given by Whitesides from Harvard University, is:

It is the science and technology of systems that process or manipulate small amounts (10−9 to 10−18 liters) of fluids, using channels with dimensions of tens to hundreds of micrometers. It offers fundamentally new capabilities in the control of concentrations of molecules in space and time [17].

The material most commonly adopted for the fabrication of microfluidic structures is poly-dimethylsiloxane (PDMS), which is optically transparent and able to support important microfluidic components, e.g., pneumatic valves; meanwhile there are other materials with research interests, e.g., polycarbonate, polyolefin, silicon, and glass. Recently paper-based (reviews by [3, 18, 19, 20, 21], and research by [22, 23, 24, 25, 26, 27, 28]) and cloth-based [29] microfluidics are drawing more attention because of the low cost, easy fabrication, and lightweight which are essential properties for POC applications. The major features of microfluidics are the small consumption of liquid sample and tiny dimensions of structures, which have significant impact on the development of biosensors, so the integration of microfluidics into biosensing techniques complies with the development of the era and generates unique features in biosensors, e.g., trace level of sample at high sensitivity.

Advertisement

4. Advantages of microfluidic-integrated biosensors

Microfluidics provide a closed and stable biosensing environment so to improve sensitivity. For on-site portable biosensors, the effect of an open environment on sensing results hugely lowers the biosensor performance. By integrating the microfluidic structures, sample processing and biosensing reactions are carried out within a closed and relatively stable environment, thus promising better sensitivity and reliability [30]. Taking the example of the application of solid-phase polymerase chain reaction (SP-PCR) in online molecular diagnosis, the development of this technique is hindered by lack of sensitive and portable on-chip optical detection technology. Hung [24] proposed a LOC device which combined the solid-phase polymerase chain reaction with supercritical angle fluorescence (SAF) microlens array embedded in a microchip. He demonstrated a high sensitivity of 1.6 copies/μL and showed comparable detection limit and linear range to off-chip detection using conventional laser scanner, and he stated this device as an on-chip highly sensitive and multiplexed pathogen detection with low-cost and compact optical components.

Microfluidic channel can efficiently, accurately, and significantly reduce the sensing area. Simulations and experiment results have shown that reducing the sensing area could shorten sensing time and increase the sensitivity with smaller sample requirement, especially at lower target concentrations [7, 11]. An increase in sensitivity of two orders of magnitude has been reported by Li et al. [31]. Meanwhile, the distribution of binding events along the sensing surface could be heterogeneous, and this could be induced by the heterogeneous in bioreceptor coverage, different alignment of bioreceptors, nonuniform concentrations of targets within samples in laminar flow, and nonuniform temperature, pressure, or other physical parameters along the sensing surface, the heterogeneity can be eliminated to minimum. Reduced sensing area also means miniaturizing sample volume which is essentially valuable to low concentration targets and rare targets with limited access.

Microfluidic structures are capable of integrating multiple functions within one device without introducing extra equipment or tools. For example, by designing and optimizing microfluidic channels, sample injection, pretreatment, and processing can be easily realized. Usually for biosensing, the modification of the biosensing surface is compulsory for specific binding of targets, and this is doable in microfluidic structures which are even more stable and more promising than manual operations. For the biosensing events, the volume and speed control of sample are achievable which provides more valuable information, e.g., binding affinity, binding rate, kinetics, etc.

Microfluidic devices are capable of automation. With or without external pumping system/equipment/tools, microfluidics is capable of integrating sample pre- and post-processing, sensing, surface modification, temperature control, EM field control, etc. The automation of microfluidic-integrated sensors and structures is reviewed by [30, 32, 33, 34]. However, the automation of whole microfluidic-integrated biosensor as one device still seems quite challenging as the liquid handling in this field is usually more complex which could involve up to dozens of solutions and operations like filtering, centrifugation, etc., together with the activity of biological samples to be considered. Partially automized microfluidic-integrated DNA biosensors are reviewed by Ansari [35]. Joung [36] presented a novel lateral flow immunosensor (LFI) for microfluidic-integrated enzyme immunosorbent assay (EIA) in POC testing (POCT), a chemiluminescent LFI-based automatic EIA system, the operation of which does not require additional steps such as mechanical fluidic control, washing, or injecting. The key concept relies on a delayed-release effect of chemiluminescent substrates (luminol enhancer and hydrogen peroxide generator) by an asymmetric polysulfone membrane (ASPM). When the ASPM was placed between the nitrocellulose membrane and the substrate pad, substrates encapsulated in the substrate pad were released after 5.3 ± 0.3 min. As a proof of concept, the high-sensitivity C-reactive protein level in human serum was detected by this sensor.

Microfluidics enables both separate and mutual processing of multiple binding assays with single or multiple samples simultaneously. For the detection of single or multiple targets in a real or complex solution, the design of the binding assay usually involves more than one kind of bioreceptors, thus meaning that the designed samples to flow over each bioreceptor spot could be different. The delivering of different kinds of samples in sequential orders can be realized by unique design of microfluidic channels, pneumatic valves [17, 37], and/or centrifugal forces [33, 34].

Microfluidic structures ensure the precise control over experimental conditions [38]. What can be precisely controlled by microfluidic structures include flow rate, sample volume, channel volume, channel height, reaction time, etc. Integration of sensors with microfluidic channels serves to reduce assay time by constraining the diffusion distance between the molecules in the sample and the sensor and to create laminar flow over the sensor to distribute target molecules broadly and uniformly [2].

Advertisement

5. The present of microfluidic-integrated biosensors

Biosensors can be classified based on target recognition events and transduction mechanisms [4]. Based on the target recognition events, biosensor receptors are included. Based on the transduction mechanisms, biosensors can be classified into optical biosensor (Raman scattering [39, 40, 41, 42, 43, 44], surface plasmon resonance (SPR) [6, 45, 46, 47], fiber Bragg grating [48, 49, 50, 51, 52, 53], fluorescent [54, 55, 56, 57, 58], chemiluminescence [36, 59]), electrochemical biosensor [60, 61, 62, 63, 64], calorimetric biosensor [6, 22, 65, 66, 67, 68, 69], and piezoelectric biosensor [70, 71, 72, 73, 74].

5.1 Target recognition

Biological targets to be detected by biosensors, especially for the detection of analytes holden by human beings/animals, could be divided into two kinds, i.e., physical parameters and physiological/biological targets. Physical parameters like the body temperature, blood pressure, heart rate, velocity, and location usually do not request a corresponding and unique bioreceptor on the biosensor, as these physical parameters usually can be detected directly by optical, electronic, and piezoelectric sensors. Analytes as physiological/biological targets, however, cannot be detected directly, because of the complex components in a real human sample, so bioreceptors are adopted for the specific recognition of these targets, including cell, antibodies, DNAs, aptamers, and molecularly imprinted polymers [4].

The most commonly adopted physiological fluids of human beings/animals are blood, which has to be collected in an invasive way, and fluids that can be collected in a noninvasive way, e.g., sweat, saliva, tears, and urine, can be used in the prediction and diagnosis of various diseases [75, 76, 77]. Comparing with other physiological fluids, saliva is the outstanding fluid with the advantages of easy accessing and large volume, but with a major disadvantage of large range of variability in components and concentrations depending on the extent of oral cleanliness; examples that have been experimentally verified are using human saliva for the detection of cytokine [78], dopamine [51], insulin [79], fetuin [80], bacterial load [81], cholesterol [25], and cortisol [82]; using tear for the detection of dopamine [83], proteomic, lipidomic, and metabolomic composition [77]; using sweat for the detection of cytokine [84] and proteomic [76]; and using urine for the detection of anticancer drugs [85], L-carnitine [86], Chlamydia trachomatis, and Neisseria gonorrhoeae [87]. Samples of sweat and tear have been significantly undeveloped until quite recent when flexible materials and flexible electronic techniques achieved some milestones [4]. Currently the most well-explored targets in human physiological fluids include electrolytes (e.g., K+, Ca2+, Na+) and major metabolites (e.g., myocardial enzyme, glucose, urea), which lack specification to diseases, indicating the general physiological conditions [4].

5.2 Transduction mechanism

So far, optical biosensors deliver the best sensitivity among the three other kinds of biosensors; electrochemical biosensors are the most popular choice as commercial-potential biosensors because of the compact size, low cost, and acceptable sensitivity; colorimetric biosensors are with a distinguished advantage of easy operation at extremely low cost but with a major disadvantage of low sensitivity; while the researches on piezoelectric biosensors are quite limited comparing with three other kinds of biosensors. Some most up-to-date researches on all fours kinds of biosensors are presented below.

5.2.1 Optical biosensors

Surface-enhanced Raman spectroscopy (SERS) and surface plasmon resonance are the two powerful optical biosensors with a unique feature of label-free sensing, as the analytes need no pre-processing to be labeled before sensing events and thus eliminate the false-positive or false-negative biosensing results induced by the labels. The first commercial product of SPR biosensor appeared in 1990 by the company of Pharmacia (named Biacore afterwards). Since then, more than 1000 papers were published annually using commercial SPR biosensors [88]. Most of these commercial SPR biosensors are bulky and only laboratory based. The development of plasmonic-based biosensors in the field of POC was reviewed in [43] together with recent advances in surface chemistry, substrate fabrication, and microfluidic integration. Here we explore a bit wider which is not limited to POC but microfluidic-integrated biosensors. In most of the researches mentioned below, the microfluidic structure usually serves as the sample handling unit.

Tunc I et al. [39] presented the molecular specificity of Raman spectroscopy together with self-assembled monolayer of metallic AuNPs to detect CA125 antibody–antigen molecules. Highly enhanced electromagnetic fields localized around neighboring AuNPs provide hot-spot construction due to the spatial distribution of SERS enhancement on the CA125 proteins at nM concentration level.

Carneiro M et al. [41] reported the detection of carcinoembryonic antigen (CEA) in SERS using two different bioreceptors for CEA, i.e., a molecularly imprinted polymer (MIP) and a natural antibody. The MIP acted as a pre-concentration scheme for the CEA, while the natural antibody signals the presence of CEA on the MIP platform. The MIP film was first incubated in the sample containing CEA and next incubated in SERS tag, which is gold nano-stars coupled to 4-aminothiophenol (4-ATP) as Raman reporter, so the MIP acted as a pre-concentration scheme for the CEA. Then the MIP was exposed to the natural CAE antibody. A sensitivity down to 1.0 ng/mL was reported.

Zhu JY et al. [89] presented a biosensor that can be used for clinical diagnosis. This biosensor is based on localized surface plasmon resonance integrated with a biomimetic microfluidic “adipose-tissue-on-chip” platform for an in situ label-free, high-throughput, and multiplexed cytokine secretion analysis of obese adipose tissue. It was stated that this system enables simultaneous measurements of pro-inflammatory (IL-6 and TNF-alpha) and anti-inflammatory (IL-10 and IL-4) cytokines secreted by the adipocytes and macrophages and identified stage-specific cytokine secretion profiles from a complex milieu during obesity progression.

In the research of [90], the plasmonic biosensor integrated the microfluidic unit for plasma separation, allows the in-line separation of plasma directly from the bloodstream without any pre-processing outside the device, and channels it to the active detection area, where inorganic cerium oxide nanoparticles function as local selective dopamine binding sites through strong surface redox reaction. A detection limit of dopamine was achieved at 100 fM concentration in simulated body fluid and 1 nM directly from blood without any prior sample preparation. This demonstration shows the feasibility of the practical implementation of the proposed plasmonic system in detection of a variety of biomarkers directly from the complex biological fluids. Li XK et al. [91] reported the plasmonic biosensor integrated a multifunctional microfluidic system with small-volume microchamber and regulation channels for reliable monitoring of cytokine secretion from individual cells for hours.

Besides the traditional plasmonic materials, graphene has recently received more and more attention in the field of both labeled and label-free sensing, because of its ability to harness electromagnetic fields, strong light-matter interaction of graphene layer, and its highly tunable optical properties [40]. Liu HP et al. [40] simulated the detection capacity of the graphene plasmonic biosensor using three-dimensional finite difference time domain method. Numerical results showed that the maximum sensitivity and figure of merit of the biosensor are 333.3 nm/RIU and 16.665 RIU, respectively.

Fluorescence is the other powerful optical biosensor which labels analytes and promises high sensitivity and specificity in target recognition. Raducanu VS et al. [56] reported a direct fluorescent signal transducer embedded in a DNA aptamer for versatile metal-ion detection. This sensor embedded with guanine-rich DNA aptamer internally coupled with Cy3 fluorescent dye that measures directly the DNA conformational changes upon metal-ion binding. Our signal transducer is environmentally sensitive that is internally coupled to the DNA aptamer. Potassium ion concentration was successfully measured in a variety of aqueous and biological test samples.

5.2.2 Electrochemical biosensors

There are plenty of researches on electrochemical biosensors, and majority of the commercialized biosensors belong to this category. Here we only present the electrochemical biosensors integrated with microfluidics that possesses both miniaturized structure and high sensitivity.

Electrode-based chemoelectrical biosensors are the most common ones. Usually a working electrode and a blank/reference electrode are designed in such biosensor, and the samples cover both electrodes and generate a measurable electrical signal. Mi SL et al. [92] reported a sensitivity up to 567 nA mM(−1) mm(−2), and the limit of detection was 4.5 M (vs. Ag/AgCl as the reference electrode) in the detection of metabolic lactate concentrations in HepG2 cells cultured with cancer drugs.

Evans D et al. [93] demonstrated a fully integrated microfluidic amperometric enzyme-linked immunosorbent assay prototype using a commercial interferon gamma release assay as a model antibody binding system. What is unique in this research is that the assay cell is based on a printed circuit board (PCB) and the microfluidic assay chemistry was engineered to take place on the Au-plated electrodes within the cell. All components were manufactured exclusively via standard commercial PCB fabrication processes. A detection limit comparable to high-end commercial systems and a short diagnosis time of 8 minutes were demonstrated.

Silicon nanowire field-effect transistor is one of the most sensitive biosensing techniques, but it is limited to analytes that carry charges. Weakly charged or uncharged analytes can hardly be detected [11]. Evans D et al. [31] presented a method of immobilizing bioreceptors on the silicon nanowire sensing surface only, comparing with the traditional methods in which a large surrounding substrate is also covered with bioreceptors, and it was proven that restricting the surface modification substantially improves the sensitivity.

Besides silicon nanowire, copper nanowire is adopted in electrochemical biosensors [94]. In [94], microfluidic chip is coupled to copper nanowires for the fast diagnosis of galactosemia in precious newborn urine samples. Galactosemia is a rare disease that is diagnosed through the identification of different metabolite profiles. The specific detection of galactose 1-phosphate (Gal 1-P), galactose (Gal), and uridyl diphosphate galactose (UDP-Gal) confirms type I, II, and III galactosemia diseases. The detection is extremely fast which is less than 350 s, required negligible urine sample consumption, and displayed impressive signal-to-noise characteristics and excellent reproducibility.

Oliveira MC et al. [95] presented an amperometric biosensor using a screen-printed electrode modified with carbon nanotubes and nickel ions for the detection of glucose, which is characterized by the chemical oxidation of carbohydrate by NiOOH. Under optimized conditions, a limit of detection 3.9 μmol/L and a limit of quantification of 13 μmol/L were reported. The effect of concomitant species such as ascorbic acid, dopamine, and uric acid was investigated, and this method was successfully applied for the determination of glucose in a commercial blood serum human (original and spiked) sample. What is unique in this research is that the microfluidic system was assembled on a 3D-printed platform constructed with acrylonitrile butadiene styrene and integrated with nine cotton threads, providing a stable flow rate.

5.2.3 Colorimetric biosensors

Plenty of reports are available on colorimetric biosensors integrated with microfluidics, e.g., [27, 28, 96, 97, 98]; most of the reports highlighted the features of cost-effectiveness and miniaturization. Different from three other kinds of biosensors, the materials adopted for the integrated microfluidic structures are usually not PDMS, but paper for the majority and cloth in some researches. Currently majority of the researches focus on the applications in food safety [22, 27, 96] and heavy metal detection [67, 99, 100] in aqueous environment. The researches in the application of biological analytes are quite limited, due to the natures of analytes and bioreceptors and the environment conditions in order to keep the activities of both analytes and bioreceptors.

Fraser LA et al. [101] presented a malaria biosensor whereby aptamers are coated onto magnetic microbeads for magnet-guided capture, wash, and detection of the biomarker. A biosensor incorporating three separate microfluidic chambers was designed to enable such magnet-guided equipment-free colorimetric detection of PfLDH. The biosensor showed high sensitivity and specificity when detecting PfLDH using both in vitro cultured parasite samples and clinical samples from malaria patients.

5.2.4 Piezoelectric biosensors

The research of piezoelectric biosensor integrated with microfluidics is quite underdeveloped so far. Possible reasons could be the lower sensitivity, poor biocompatibility, and complicated fabrication.

Yamaguchi M. [82] proposed a mass sensor based on mechanical resonance that incorporates a disk-shaped mechanical resonator, a separate piezoelectric element used to excite vibrations in the resonator, and a microfluidic mechanism. Electrical power is used to actuate the piezoelectric element, leaving the resonator free from power lines. This sensor was reported to be suitable to analyze the concentration of a salivary hormone, cortisol in human saliva samples.

Advertisement

6. Future research interests

Future possible research interests in the field of microfluidic-integrated biosensors are proposed as the following:

  • Exploration of materials for both microfluidics and nanofluidics in different application scenarios. Besides PDMS, the exploration of other materials, e.g., engineering polymers, traditional glass, silicon, or metal, in special applications that requires high chemical stability, high thermal stability, unique optical properties, and/or special mechanical properties.

  • Fabrication of microfluidics and nanofluidics and structures (e.g., valves, mixers).

  • Microfluidics with high chemical and thermal stability for special applications.

  • Integration of microfluidics and nanofluidics with sensors to form complete and functional systems that require no professional operations and ease in applications, e.g., LOC, etc.

  • Integration of microfluidics with data processing algorithms. The application of machine learning in sensing data processing could enhance the performance of biosensors in specialized environments.

  • Integration of microfluidics with communication techniques. Synchronization of sensing data with relevant users, remote control of the biosensors, and big data analysis of special sensing networks can be realized.

Advertisement

7. Conclusions

The state-of-the-art advances in biosensor development based on microfluidic technology have been reviewed in the book chapter with focus on the applications, challenges, and possible future research interests for each type of biosensor. It can be envisioned that microfluidic-based biosensors will remain a hot topic of investigations because of the ever-increasing demands in various applications ranging from industry to biomedical detection. The interests in microfluidic-integrated biosensors promise even more prospective future in these areas. It is applications in wearable biosensor; portable biosensor can be explored in the future with enhanced sensitivity, improved stability, and miniaturized structure.

Advertisement

Acknowledgments

This research was supported by Zhejiang Provincial Natural Science Foundation of China under Grant No. LQ19F050003 as well as Ningbo Science and Technology Bureau under Service Industry Science & Technology Programme with project code 2019F1030.

Advertisement

Conflict of interest

The authors declare no conflict of interest.

References

  1. 1. Schasfoort RBM, Tudos AJ. Handbook of Surface Plasmon Resonance. Royal Soc Chemistry; 2008
  2. 2. Che C et al. Activate capture and digital counting (AC + DC) assay for protein biomarker detection integrated with a self-powered microfluidic cartridge. Lab on a Chip. 2019;19(23):3943-3953
  3. 3. Vashist SK et al. Emerging technologies for next-generation point-of-care testing. Trends in Biotechnology. 2015;33(11):692-705
  4. 4. Tu J et al. The Era of Digital Health: A Review of Portable and Wearable Affinity Biosensors. Advanced Functional Materials. 2019:1906713
  5. 5. Steinhubl SR, Muse ED, Topol EJ. The emerging field of mobile health. Science Translational Medicine. 2015;7(283):283rv3
  6. 6. Wang J et al. Highly sensitive multipoint real-time kinetic detection of surface plasmon bioanalytes with custom CMOS cameras. Biosensors and Bioelectronics. 2014;58:157-164
  7. 7. Ciampi S, Harper JB, Gooding JJ. Wet chemical routes to the assembly of organic monolayers on silicon surfaces via the formation of Si–C bonds: Surface preparation, passivation and functionalization. Chemical Society Reviews. 2010;39(6):2158-2183
  8. 8. Liang G et al. Fiber Optic Surface Plasmon Resonance-Based Biosensor Technique: Fabrication, Advancement, and Application. Critical Reviews in Analytical Chemistry. 2016:213-223
  9. 9. Mok J et al. Digital microfluidic assay for protein detection. Proceedings of the National Academy of Sciences. 2014;111(6):2110-2115
  10. 10. Sun J, Wang S, Gao F. Covalent surface functionalization of semiconducting polymer dots with beta-cyclodextrin for fluorescent Ratiometric assay of cholesterol through host-guest inclusion and FRET. Langmuir. 2016;32(48):12725-12731
  11. 11. Shen M-Y, Li B-R, Li Y-K. Silicon nanowire field-effect-transistor based biosensors: From sensitive to ultra-sensitive. Biosensors and Bioelectronics. 2014;60:101-111
  12. 12. Chu CJ et al. Improving nanowire sensing capability by electrical field alignment of surface probing molecules. Nano Letters. 2013;13(6):2564-2569
  13. 13. Schneider CS et al. Surface plasmon resonance as a high throughput method to evaluate specific and non-specific binding of nanotherapeutics. Journal of Controlled Release. 2015;219:331-344
  14. 14. Wuethrich A, Howard CB, Trau M. Geometric optimisation of electrohydrodynamic fluid flows for enhanced biosensing. Microchemical Journal. 2018;137:231-237
  15. 15. Arreola J et al. Surface functionalization for spore-based biosensors with organosilanes. Electrochimica Acta. 2017;241:237-243
  16. 16. Platt GW et al. Allergen immobilisation and signal amplification by quantum dots for use in a biosensor assay of IgE in serum. Biosensors and Bioelectronics. 2014;52:82-88
  17. 17. Whitesides GM. The origins and the future of microfluidics. Nature. 2006;442(7101):368-373
  18. 18. Mross S et al. Microfluidic enzymatic biosensing systems: A review. Biosensors and Bioelectronics. 2015;70:376-391
  19. 19. Yetisen AK, Akram MS, Lowe CR. Paper-based microfluidic point-of-care diagnostic devices. Lab on a Chip. 2013;13(12):2210-2251
  20. 20. Li X, Ballerini DR, Shen W. A perspective on paper-based microfluidics: Current status and future trends. Biomicrofluidics. 2012;6(1):011301
  21. 21. Nie Z et al. Integration of paper-based microfluidic devices with commercial electrochemical readers. Lab on a Chip. 2010;10(22):3163-3169
  22. 22. Aksorn J, Teepoo S. Development of the simultaneous colorimetric enzymatic detection of sucrose, fructose and glucose using a microfluidic paper-based analytical device. Talanta. 2020;207:120302
  23. 23. Chethana K et al. Fiber bragg grating sensor based device for simultaneous measurement of respiratory and cardiac activities. Journal of Biophotonics. 2017;10(2):278-285
  24. 24. Hung TQ et al. A novel lab-on-chip platform with integrated solid phase PCR and supercritical angle fluorescence (SAF) microlens array for highly sensitive and multiplexed pathogen detection. Biosensors and Bioelectronics. 2017;90:217-223
  25. 25. Lee YJ et al. Enzyme-loaded paper combined impedimetric sensor for the determination of the low-level of cholesterol in saliva. Sensors and Actuators B: Chemical. 2018;271:73-81
  26. 26. López Marzo AM et al. All-integrated and highly sensitive paper based device with sample treatment platform for Cd2+ immunodetection in drinking/tap waters. Analytical Chemistry. 2013;85(7):3532-3538
  27. 27. Mooltongchun M, Teepoo S. A simple and cost-effective microfluidic paper-based biosensor analytical device and its application for hypoxanthine detection in meat samples. Food Analytical Methods. 2019;12(12):2690-2698
  28. 28. Rafatmah E, Hemmateenejad B. Colorimetric and visual determination of hydrogen peroxide and glucose by applying paper-based closed bipolar electrochemistry. Microchimica Acta. 2019;186(11)
  29. 29. Guan W, Liu M, Zhang CS. Electrochemiluminescence detection in microfluidic cloth-based analytical devices. Biosensors & Bioelectronics. 2016;75:247-253
  30. 30. Alam MK et al. Recent advances in microfluidic technology for manipulation and analysis of biological cells (2007-2017). Analytica Chimica Acta. 2018;1044:29-65
  31. 31. Li B-R et al. Biomolecular recognition with a sensitivity-enhanced nanowire transistor biosensor. Biosensors and Bioelectronics. 2013;45:252-259
  32. 32. Maceiczyk RM, Lignos IG, DeMello AJ. Online detection and automation methods in microfluidic nanomaterial synthesis. Current Opinion in Chemical Engineering. 2015;8:29-35
  33. 33. Burger R, Amato L, Boisen A. Detection methods for centrifugal microfluidic platforms. Biosensors and Bioelectronics. 2016;76:54-67
  34. 34. Torres Delgado SM et al. Wirelessly powered and remotely controlled valve-array for highly multiplexed analytical assay automation on a centrifugal microfluidic platform. Biosensors and Bioelectronics. 2018;109:214-223
  35. 35. Ansari MIH et al. Microfluidic-integrated DNA nanobiosensors. Biosensors and Bioelectronics. 2016;85:247-260
  36. 36. Joung H-A, Oh YK, Kim M-G. An automatic enzyme immunoassay based on a chemiluminescent lateral flow immunosensor. Biosensors and Bioelectronics. 2014;53:330-335
  37. 37. Pradeep A et al. Automated and programmable electromagnetically actuated valves for microfluidic applications. Sensors and Actuators a-Physical. 2018;283:79-86
  38. 38. Halldorsson S et al. Advantages and challenges of microfluidic cell culture in polydimethylsiloxane devices. Biosensors and Bioelectronics. 2015;63:218-231
  39. 39. Tunc I, Susapto HH. Label-free detection of ovarian Cancer antigen CA125 by surface enhanced Raman scattering. Journal of Nanoscience and Nanotechnology. 2020;20(3):1358-1365
  40. 40. Liu HP et al. A 3D multilayer curved plasmonic coupling array with abundant and uniform hot spots for surface-enhanced Raman scattering. Journal of Physics D: Applied Physics. 2020:53(5)
  41. 41. Carneiro M et al. Dual biorecognition by combining molecularly-imprinted polymer and antibody in SERS detection. Application to carcinoembryonic antigen. Biosensors & Bioelectronics. 2019:146
  42. 42. Lee T et al. Single functionalized pRNA/gold nanoparticle for ultrasensitive MicroRNA detection using electrochemical surface-enhanced Raman spectroscopy. Advanced Science.
  43. 43. Li ZH et al. Plasmonic-based platforms for diagnosis of infectious diseases at the point-of-care. Biotechnology Advances. 2019;37(8):107440
  44. 44. Sakir M et al. Photocatalytic green fabrication of Au nanoparticles on ZnO nanorods modified membrane as flexible and photocatalytic active reusable SERS substrates. Colloids and Surfaces a-Physicochemical and Engineering Aspects. 2020;585
  45. 45. Bhardwaj H, Sumana G, Marquette CA. A label-free ultrasensitive microfluidic surface Plasmon resonance biosensor for Aflatoxin B1 detection using nanoparticles integrated gold chip. Food Chemistry. 2020;307:125530
  46. 46. Das CM et al. A theoretical insight into the use of anti-reflective coatings for the upliftment of sensitivity of surface plasmon resonance sensors. Optics Communications. 2020;458
  47. 47. Farmani H, Farmani A, Biglari Z. A label-free graphene-based nanosensor using surface plasmon resonance for biomaterials detection. Physica E-Low-Dimensional Systems & Nanostructures. 2020;116
  48. 48. Chen XY et al. In-situ detection of small biomolecule interactions using a plasmonic tilted fiber grating sensor. Journal of Lightwave Technology. 2019;37(11):2792-2799
  49. 49. He YL et al. Fiber brag grating monitoring of a morphing wing based on a polyvinyl chloride reinforced silicone substrate. Optical Fiber Technology. 2019;50:145-153
  50. 50. Lao JJ et al. Gold nanoparticle-functionalized surface Plasmon resonance optical Fiber biosensor: In situ detection of thrombin with 1 n.M detection limit. Journal of Lightwave Technology. 2019;37(11):2748-2755
  51. 51. Lobry M et al. Non-enzymatic D-glucose plasmonic optical fiber grating biosensor. Biosensors & Bioelectronics. 2019;142
  52. 52. Loyez M et al. Functionalized gold electroless-plated optical fiber gratings for reliable surface biosensing. Sensors and Actuators B: Chemical. 2019;280:54-61
  53. 53. Sypabekova M et al. Functionalized etched tilted fiber Bragg grating aptasensor for label-free protein detection. Biosensors & Bioelectronics. 2019;146
  54. 54. Fan XC et al. Target-induced autonomous synthesis of G-quadruplex sequences for label-free and amplified fluorescent aptasensing of mucin 1. Sensors and Actuators B: Chemical. 2020;304
  55. 55. Li J et al. Glucose assay based on a fluorescent multi-hydroxyl carbon dots reversible assembly with phenylboronic acid brush grafted magnetic nanoparticles. Sensors and Actuators B: Chemical. 2020;304
  56. 56. Raducanu VS et al. A direct fluorescent signal transducer embedded in a DNA aptamer paves the way for versatile metal-ion detection. Sensors and Actuators B: Chemical. 2020;304
  57. 57. Tang YY et al. A robust OFF-ON fluorescent biosensor for detection and clearance of bacterial endotoxin by specific peptide based aggregation induced emission. Sensors and Actuators B: Chemical. 2020;304
  58. 58. Zhang JY et al. F-containing initiatior for ultrasensitive fluorescent detection of lung cancer DNA via atom transfer radical polymerization. Analytica Chimica Acta. 2020;1094:99-105
  59. 59. Yu J et al. Microfluidic paper-based chemiluminescence biosensor for simultaneous determination of glucose and uric acid. Lab on a Chip. 2011;11(7):1286-1291
  60. 60. Hu HL et al. Ni hierarchical structures supported on Titania nanowire arrays as efficient nonenzymatic glucose sensor. Journal of Nanoscience and Nanotechnology. 2020;20(5):3246-3251
  61. 61. Hui YY et al. An electrochemical aptasensor based on DNA-AuNPs-HRP nanoprobes and exonuclease-assisted signal amplification for detection of aflatoxin B-1. Food Control. 2020;109
  62. 62. Peyman H, Roshanfekr H, Ansari S. DNA-based electrochemical biosensor using chitosan-carbon nanotubes composite film for biodetection of Pirazon. Eurasian Chemical Communication. 2020;2(2):213-225
  63. 63. Sundar S, Kwon SJ, Venkatachalam G. Magneto-biosensor for the detection of uric acid using citric acid-capped Iron oxide nanoparticles. Journal of Nanoscience and Nanotechnology. 2020;20(4):2144-2153
  64. 64. Vathani AM et al. Fabrication of Al-TiO2 thin film electrode by spray pyrolysis technique for urea sensing. Journal of Nanoscience and Nanotechnology. 2020;20(5):2887-2892
  65. 65. Fu QQ et al. Ambient light sensor based colorimetric dipstick reader for rapid monitoring organophosphate pesticides on a smart phone. Analytica Chimica Acta. 2019;1092:126-131
  66. 66. Huang LT, Li ZH, Guo LQ. Colorimetric assay of acetylcholinesterase inhibitor tacrine based on MoO2 nanoparticles as peroxidase mimetics. Spectrochimica Acta Part a-Molecular and Biomolecular Spectroscopy. 2020;224
  67. 67. Jia M et al. Extended GR-5 DNAzyme-based autonomous isothermal Cascade machine: An efficient and sensitive one-tube colorimetric platform for Pb2+ detection. Sensors and Actuators B: Chemical. 2020;304
  68. 68. Kong LB et al. A novel smartphone-based CD-spectrometer for high sensitive and cost-effective colorimetric detection of ascorbic acid. Analytica Chimica Acta. 2020;1093:150-159
  69. 69. Wei SQ et al. Exponential amplification reaction and triplex DNA mediated aggregation of gold nanoparticles for sensitive colorimetric detection of microRNA. Analytica Chimica Acta. 2020;1095:179-184
  70. 70. Kim KI et al. Influence of temperature and humidity on the detection of benzene vapor by a piezoelectric crystal sensor. Instrumentation Science & Technology. 2019;47(4):436-447
  71. 71. Pohanka M. Piezoelectric Immunosensor for the determination of C-reactive protein. International Journal of Electrochemical Science. 2019;14(9):8470-8478
  72. 72. Urdinola KB et al. In-Silico Prediction on the MSAMS-Assisted Immobilization of Bovine Serum Albumin on 10 MHz Piezoelectric Immunosensors. Journal of Molecular and Engineering Materials. 2019;7(1-2)
  73. 73. Yuan M et al. Piezoelectric arsenite aptasensor based on the use of a self-assembled mercaptoethylamine monolayer and gold nanoparticles. Microchimica Acta. 2019;186(5)
  74. 74. Zamora-Sequeira R et al. What are the Main Sensor Methods for Quantifying Pesticides in Agricultural Activities? A Review. Molecules. 2019:24(14)
  75. 75. Katchman BA et al. Eccrine Sweat as a Biofluid for Profiling Immune Biomarkers. Proteomics Clinical Applications. 2018:12(6)
  76. 76. Adewole OO et al. Proteomic profiling of eccrine sweat reveals its potential as a diagnostic biofluid for active tuberculosis. Proteomics Clinical Applications. 2016;10(5):547-553
  77. 77. Hagan S, Martin E, Enriquez-de-Salamanca A. Tear fluid biomarkers in ocular and systemic disease: Potential use for predictive, preventive and personalised medicine. Epma Journal. 2016;7
  78. 78. Belstrøm D et al. Salivary cytokine levels in early gingival inflammation. Journal of Oral Microbiology. 2017;9(1)
  79. 79. Viswanath B et al. Recent trends in the development of diagnostic tools for diabetes mellitus using patient saliva. Trends in Analytical Chemistry. 2017;89:60-67
  80. 80. Sánchez-Tirado E et al. Magnetic multiwalled carbon nanotubes as nanocarrier tags for sensitive determination of fetuin in saliva. Biosensors and Bioelectronics. 2018;113:88-94
  81. 81. Ana C et al. Dental caries and bacterial load in saliva and dental biofilm of type 1 diabetics on continuous subcutaneous insulin infusion. Journal of Applied Oral Science. 2018;26
  82. 82. Yamaguchi M. Microfluidic line-free mass sensor based on an antibody-modified mechanical resonator. Micromachines. 2018;9(4):13
  83. 83. Sharma N et al. Dopamine levels in human tear fluid. Indian Journal of Ophthalmology. 2019;67(1):38-41
  84. 84. Hladek MD et al. Using sweat to measure cytokines in older adults compared to younger adults: A pilot study. Journal of Immunological Methods. 2018;454:1-5
  85. 85. Chandra P et al. Separation and simultaneous detection of anticancer drugs in a microfluidic device with an amperometric biosensor. Biosensors and Bioelectronics. 2011;28(1):326-332
  86. 86. Andrianova MS et al. CMOS-compatible biosensor for L-carnitine detection. Biosensors and Bioelectronics. 2018;119:48-54
  87. 87. Soler M et al. Multiplexed nanoplasmonic biosensor for one-step simultaneous detection of chlamydia trachomatis and Neisseria gonorrhoeae in urine. Biosensors and Bioelectronics. 2017;94:560-567
  88. 88. Myszka DG. Handbook of surface Plasmon resonance 2nd edition foreword to the 1st edition. In: Schasfoort RBM, editor. Handbook of surface Plasmon resonance, 2nd edition. 2017. pp. V-IX
  89. 89. Zhu JY et al. An integrated adipose-tissue-on-chip nanoplasmonic biosensing platform for investigating obesity-associated inflammation. Lab on a Chip. 2018;18(23):3550-3560
  90. 90. Vazquez-Guardado A et al. Enzyme-free plasmonic biosensor for direct detection of neurotransmitter dopamine from whole blood. Nano Letters. 2019;19(1):449-454
  91. 91. Li XK et al. Label-Free Optofluidic Nanobiosensor Enables Real-Time Analysis of Single-Cell Cytokine Secretion. Small. 2018:14(26)
  92. 92. Mi SL et al. An integrated microchannel biosensor platform to analyse low density lactate metabolism in HepG2 cells in vitro. RSC Advances. 2019;9(16):9006-9013
  93. 93. Evans D et al. A novel microfluidic point-of-care biosensor system on printed circuit board for cytokine detection. Sensors. 2018;18(11)
  94. 94. Garcia M, Alonso-Fernandez J, Escarpa A. Copper nanowires immobilized on the boards of microfluidic chips for the rapid and simultaneous diagnosis of Galactosemia diseases in Newborn urine samples. Analytical Chemistry. 2013;85(19):9116-9125
  95. 95. Oliveira MC et al. Nonenzymatic sensor for determination of glucose in blood plasma based on nickel oxyhydroxide in a microfluidic system of cotton thread. Journal of Electroanalytical Chemistry. 2019;840:153-159
  96. 96. Chungchai W et al. Development of a novel three-dimensional microfluidic paper-based analytical device (3D-mu PAD) for chlorpyrifos detection using graphene quantum-dot capped gold nanocomposite for colorimetric assay. International Journal of Environmental Analytical Chemistry
  97. 97. Fakhri N et al. Paper based colorimetric detection of miRNA-21 using Ag/Pt nanoclusters. Spectrochimica Acta Part a-Molecular and Biomolecular Spectroscopy. 2020;227
  98. 98. Li F et al. High-resolution temporally resolved chemiluminescence based on double-layered 3D microfluidic paper-based device for multiplexed analysis. Biosensors & Bioelectronics. 2019;141
  99. 99. Hossain SMZ, Brennan JD. Beta-Galactosidase-based colorimetric paper sensor for determination of heavy metals. Analytical Chemistry. 2011;83(22):8772-8778
  100. 100. Lin Y et al. Detection of heavy metal by paper-based microfluidics. Biosensors and Bioelectronics. 2016;83:256-266
  101. 101. Fraser LA et al. A portable microfluidic Aptamer-tethered enzyme capture (APTEC) biosensor for malaria diagnosis. Biosensors and Bioelectronics. 2018;100:591-596

Written By

Jing Wang, Yong Ren and Bei Zhang

Submitted: November 26th, 2018 Reviewed: February 28th, 2020 Published: May 20th, 2020