Biosensors & Biochips for Sustainable Future

B A S I C   L E V E L

Biochips appeared as an innovative microtechnology platform for analysis of bio-molecule in the 1980s.  

Contents

 

Biosensors & Biochips: An overview

Biochips appeared as an innovative microtechnology platform for analysis of bio-molecule in the 1980s. A variety of technologies, such as life sciences, information technology, microelectronics and micromechanics, are involved in the underlying technologies. Biochips are considered important potential instruments in modern life science research, medical diagnosis, drug discovery, food safety monitoring and agriculture as high-performance, miniaturized, automated and cost-effective features. Biochips are expected to allow the speed and scope of the analytical process to be dramatically increased and to provide enormous economic value. Further more, in recent years, numerous governments and industrial companies in the world have invested heavily in this sector. Biochip technology is just in its early evolution for now. This is an area which is ever-changing. The future for biochip research and development is bright. There is furious competition in this area.

In biomedical and life science research, the miniaturization of chemical and biomedical laboratory processes on microchips is a rapidly expanding field. Lab-on-chip technologies will bring a lot of benefits over their macro-sized counterparts. In particular, higher surface-to-volume ratios result in reduced chemical requirements, reduced waste, better control, rapid processing and significant ability for parallel processing and process incorporation. Lab-on-chip technologies has the potential to have a significant socio-economic impact. In laboratory medicine, completely integrated microdevices for chemical synthesis and disease diagnosis offer a scientific breakthrough and a paradigm change in chemical processing. The human genome project has made a huge contribution to this technology.

In the field of analytics, biosensors allow major innovations that are both facilitating and facilitated by developments in synthetic biology. The potential of biosensors to identify a wide range of molecules easily and precisely makes them highly important to a variety of industrial, medical, ecological, and science applications. Biosensor design strategies are as numerous as their applications, with major groups of biosensors including nucleic acids, proteins, and transcription factors. Based on the expected use, and the parameters required for optimum performance, each of these types of biosensors has advantages and limitations. Especially, considerations such as ligand specificity, sensitivity, dynamic range, functional range, output mode, activation time, ease of use, and ease of engineering must be considered when choosing the design of the biosensor.

Blueprints for Biosensors: Design & Operation

Biosensors are sensors that transform bio-recognition processes through a physico-chemical transducer into observable signals, with electronic and optical techniques as two main transducers. The creation of biosensors addresses today’s rapidly rising need for clinical diagnostics. A combination of advantages is brought on by the use of biosensors. Biosensors, first, are highly sensitive. This is because biomolecules have a high affinity for their targets, for example, antibodies catch antigens with a dissociation constant at the nanomolar scale, and DNA – DNA interactions are so much stronger than antigen-antibody. Second, biological recognition is typically very selective. The enzyme and substrate are much like a lock and a key, for example. Such high selectivity frequently leads to biosensors that are selective. Third, the production of inexpensive, integrated, and ready-to-use biosensor devices has become relatively easy to develop due to the development of the modern electronic industry. The ability to detect pathogens or perform genetic analysis in hospitals is certainly improved by these biological sensors; more importantly, they are especially useful for small clinics and even point-of-care analysis.

For biosensors with clinical applications, a range of new techniques have been developed. Biosensors are, in general, analytical devices constructed of an element of biological recognition and an optical/electronic transducer. The biological element is responsible for the capture of solution analytes and the transducer transforms the binding event to a measurable signal variation. By the nature of recognition, enzyme-based biosensors, immunological biosensors, and DNA biosensors, could categorize the type of biosensors. In addition, electronic biosensors (electrical or electrochemical), optical biosensors (fluorescent, surface plasmon resonance, or Raman), and piezoelectric biosensors (quartz crystal microbalance) are available depending on the type of transducer.

Electrochemical biosensors

For biological sensing, where electrodes function as either electron donors or electron acceptors, electrochemical techniques are particularly useful. Extensive electrochemical experiments have shown that the Marcus electron-transfer theory also complies with heterogeneous electron transfer between electrodes and surface-confined redox molecules, similar to donor-acceptor pairs in homogeneous solutions. This means that small distance changes in redox surface-confined molecules can cause wide variations in the heterogeneous electron-transfer rates that are supposed to translate into detectable changes of electrochemical signals. Hellinga and co-workers, for example, suggested an electrochemical sensing strategy that exploits protein ligand-mediated hinge-bending motions. A gold electrode was first coated with a self-assembled monolayer (SAM), which gives a versatile platform for site-specific protein immobilization. The maltose-binding protein (MBP) was then bound to the surface of the gold electrode with a particular orientation as the redox reporter group of ruthenium (Ru(II)) is fixed at a certain range above the electrode. As the ligand maltose binds to the active site, the Ru(II) reporter moves away from the electrode by causing a hinge-bending motion of MBP (Figure 1).

Figure 1. Construction and operation of electrochemical biosensor

This maltose-binding induced distance change causes concentration-dependent decreases in electrochemical signals, thus providing a way for maltose to be electronically sensed. The use of this highly generalized sensing approach to detect various analytes with a family of proteins or enzymes undergoing ligand-binding induced conformational changes has also been shown.

Enzyme-based biosensors

The first biosensors ever documented were glucose oxidase (GOD)-based biosensors, established by Clark and Lyons in 1962. Hyperglycemia, a chronically raised concentration of blood glucose, is common for diabetes mellitus. As a result, regular control of their blood glucose concentration is essential for diabetic patients. The benefit of electrochemistry coupled with enzyme catalysis is this biosensor, and its newer versions. An electrode immobilized with GOD was Clark’s biosensor. The oxidized form of GOD interacts with glucose in the presence of glucose and produces gluconic acid and reduced GOD, with two electrons and two protons involved. As dissolved oxygen reacts with reduced GOD, this glucose oxidation also consumes oxygen in the solution, thereby producing hydrogen peroxide and oxidized GOD, and lowering oxygen pressure. As a result, by electrochemically sensing oxygen with a Clark oxygen electrode, the electrode can detect the glucose. This kind of sensor is considered a biosensor of the “first generation.” The Yellow Springs Instrument Company (Ohio, USA) marketed this first-generation biosensor in the 1970s.

The second-generation biosensor substitutes the naturally-existing substrate, oxygen, with small artificial redox molecules that act as redox mediators and exchange electrons between electrodes and enzymes. To improve the sensor efficiency, that is, sensitivity and signal-to-noise ratio, a variety of soluble redox molecules, such as ferrocene, thionine, methylene blue, methyl viologen, were used. These mediators were initially dissolved in a solution. They obtain electrons from the electrodes and then, or vice versa, these electrons are shuttled to the redox center of the enzymes. Immobilized mediators were suggested as a step forward, in order to enhance reagentless biosensors. For example, for hydrogen peroxide, Ruan et al in 1998 documented a reagentlesssolid-state sensor. Gold electrodes were first modified with L-cysteine, and then multilayers of horseradish peroxidase (HRP) were connected by glutaraldehyde to the amine group of cysteine, and thionine was further linked to the enzyme by the same chemical link. As a result, the gold electrode was immobilized by both the enzyme and the mediator, which could detect hydrogen peroxide sensitively in the test solution without further reagent addition. An essential advantage of this configuration of the biosensor is that the mediator is fixed on the electrode surface, thereby preventing the diffusion problem.

An alternative solution that included the use of redox polymers was stated by Heller and co-workers. First, they prepared a doped polymer with Os2+complex. This type of polymer functions as a “molecular wire” and exchanges electrons between the enzyme and the electrode. The Os-polymer and glucose oxidase are then co-immobilized on the carbon electrode, which generates a sensitive response to the presence of glucose. They were able to make almost 100 % immobilized enzyme molecules electroactive by using these redox polymers, which contributed to a very high sensitivity method of glucose detection.

The commercialization of the enzyme-based second-generation biosensor was quite successful. In 1987, MediSense was established and the pensized ExactechTM glucose sensors were released. This success has led to a health care revolution for diabetic patients. Instead of traveling to hospitals, they were able to control their concentration of blood glucose at home. The MediSense and later amperometric biosensor systems consist of GOD-coated disposable, screen-printed carbon electrodes and mediators (test strips). The sensor starts to function when a droplet of blood is applied to the test strip and records the amperometric response, which is transformed to a digit displayed on the LCD, indicating glucose concentration.

More recently, by designing a reconstructed GOD enzyme, Xiao et al (2003) published a new glucose biosensor generation. They first prepared apo-GOD free of the cofactor of flavin adenine dinucleotide (FAD), then functionalized and reconstructed a 1.4-nm gold nanoparticle with FAD into the apo-GOD. By using a dithiol monolayer, such a reconstructed enzyme was aligned with gold electrodes (Figure 2). They demonstrated that this artificial enzyme’s electron transfer turnover is as high as 5000 s-1, approximately 8-fold higher than the normal enzyme (700 s-1). The gold nanoparticle in this system serves as an electron relay for the electrical wiring of the enzyme’s redox center. In this area, the glucose biosensor established by Xiao et al represents a new path, free from any mediator and highly sensitive. More recently, by using single wall carbon nanotubes (SWNTs) instead of gold nanoparticles, Willner’s group documented a modified version of this sensor and realized a similarly superior efficiency. Although there is still no commercialization of this technology, it is expected that state-of-the-art biosensors will be further improved.

Figure 2 Construction and operation of enzyme – based biosensor

Immunological biosensor

To identify environmental or clinically important targets, immunological biosensors depend on a highly specific immunological system, i.e., antibodies and antigens. In reality, immunological biosensors are a modern variant of the enzyme-linked immunosorbent assay (ELISA), with lower costs, increased speed and convenience of service, and sensitivity that is comparable or even higher.

Among the most common ones are electrochemical immunological biosensors. Two types of immunological biosensors are available. First, the electrode is immobilized with a capture antibody, which catches a particular target antigen. Via a secondary antibody tagged with redox molecules or enzymes, signal transduction is achieved. Second, an electrode antigen is immobilized, which detects specific antibodies.

Ju and co-workers established a carcinoembryonic antigen (CEA) amperometric immunological biosensor. Thionine and HRP-labeled CEA antibodies were co-immobilized on a glassy carbon electrode crosslinked with glutaraldehyde. In the solution, which was coupled to the electrode reaction of thionine, HRP catalytically reduced hydrogen peroxide, leading to a catalyzed signal. The redox center of HRP was partly blocked by catching CEA, leading to attenuation of amperometric signals.

Rusling and colleagues have recently taken advantage of SWNTs to enhance immunological biosensor performance (Figure 3).

Figure 3. Construction and operation of immunological biosensor

By using metal mediated self-assembly, they designed vertically aligned arrays of SWNTs (SWNT forest) on pyrolytic graphite electrodes. Anti-HSA, using EDC/NHS, was then covalently bound to the carboxylated ends of the SWNT forest. The electrode was further incubated with a secondary HRP-labelled anti-HSA antibody after catching the HSA target. The HSA target in the test solution can be identified based on the catalytic signal of HRP for hydrogen peroxide. The detection sensitivity, which was around 1 nM, was dramatically improved by the use of SWNT forests. This was probably due to the improved reactivity of electron transfer of HRP encapsulated in SWNT forests.

One of the most relevant clinical tools has been immunological assays. However, existing assay methods, such as ELISA, require large and costly instruments as well as well-trained specialists. For the development of cheap, miniaturized, and compact devices, electrochemical methods are well adapted. As a result, the development of electrochemical immunological biosensors to meet field and point-of-care analysis is highly desirable. It is important to mention that the use of disposable screen-printed electrodes could be crucial towards this goal, comparable to glucose biosensors. In order to carry out high-throughput (HTS) assays, it is also important to establish antibody microarrays based on electrochemistry.

DNA biosensors

There has been tremendous scientific and technological interest in the identification of DNA hybridization events. The rapidly growing interest in chip-based clinical diagnosis has particularly demonstrated this significance. Therefore , a variety of techniques, including optical, acoustic and electronic approaches, have been developed over the years. In past decades, fluorescent detection has dominated state-of-the-art genosensors among them . Electrochemical methods, however, which have proven effective in simple chemical species, especially metal ions, have attracted increasingly growing interested in biologically related species detection applications.

The benefits of electronic detection include: 1) electrochemical detection is typically inexpensive thus enabling highly sensitive and rapid screening; 2) several electroactive labels, e.g. metallocenes, are stable and environmentally insensitive, unlike fluorophores that often have “photo-bleaching” problems; 3) appropriate molecular design and synthesis that generate a variety of derivatives, each with a specific redox potential, have made it possible to label ‘multi-color’; 4) The rapidly established silicon industry has paved the way for the mass production of integrated circuits, making electronic detection particularly appropriate and compatible with microarray-based technologies; 5) The exponential growth of interfacial science and technology has unraveled mysteries in the precise control of surface properties that are one of the key barricades in bioelectronic applications.

At moderate applied voltages, DNA itself is electrochemically silent, while significant interferences are predicted at high voltages that cause DNA bases to be oxidized/reduced (. Millan was the first to suggest sequence-selective DNA target detections based on electroactive hybridization indicators that provide electronic signals and double and single-stranded DNA discrimination. “Sandwich” type detections were suggested in an effort to reduce the high background derived from the minor binding of hybridization indicators to ssDNA. A DNA strand possessing an electroactive label has been introduced to act as the signaling molecule in addition to an immobilized DNA probe. Similarly, with nanoparticle probes, Park and collegues in 2002 have developed an array-based electrical DNA detection that demonstrates high sensitivity and selectivity. A technology based on the relatively high oxidation activity of guanine and its cooperation by exogenous redox catalysts was developed by Thorp one year later. The discrimination of ds/ss is obtained by the fact that guanine has relatively low electron transfer reactivity in duplexes, due to the steric effect. In the detection of PCR products, this method is highly sensitive, but relatively poor in discriminating hybridization events. Moreover, this method is only possible on ITO surfaces so far, because the high oxidation potential still excludes the use of gold.

Despite progress, the development of an all-in-one (i.e. reagentless) sensor that specifically signals target capture is still highly important (i.e., obviating further treatment with either signal molecules or hybridization indicators). A viable means to this end is provided by DNA or RNA aptamers. Aptamers are well-structured DNA or RNA that have high affinity and selectivity for particular targets as well as natural enzymes, thus showing superior robustness to fragile enzymes. They have been a very promising tool for therapy and diagnosis. Until then, for virtually any given target, the well-developed in vitro selection was able to produce aptamers. In view of these benefits, oligonucleotide aptamers are predicted to be the biosensing components of the next generation. An easy, organized hairpin-like DNA with an electroactive label (electronic DNA hairpin) was used by Fan and collegues as the building block to define hybridization events (Figure 4).

Figure 4. Construction and operation of DNA biosensor

Hairpin-like DNA was an incredibly fascinating aptamer that forms the basis of homogeneous hybridization recognition of fluorescent “molecular beacons”. The DNA sequence has been designed so that in the absence of targets, this “beacon” is in the near state while it will be “turned on” when it reaches its particular gene target. The presence of the design of the stem-loop in the structure offers an on/off switch as well as a stringency to differentiate against single DNA hybridization mismatch. A thiolated terminus gives a sticky end to the gold surface of this electronic DNA hairpin, while a ferrocene tag transduces electronic signals at the other end. The initial hairpin localizes the ferrocene proximal to the electrode surface, thus allowing interfacial electron transfer. After hybridization, the formation of the linear duplex structure disrupts the hairpin and forces apart the ferrocene and the electrode. This significant distance change (up to a few nm) effectively blocked the interfacial electron transfer and leads to the diminution of corresponding electrochemical current signals. This strategy offers the opportunity to identify 10 pM DNA targets. More importantly, such a design takes advantage of integrating within a single surface-confined hairpin structure the capturing part (probe sequence) and the signaling part (electroactive species). In contrast to most previously proposed solid-state DNA sensors, this design is therefore effectively reagentless, i.e. no exogenous reagent is required during the recognition process apart from DNA targets. This provides the basis for the development of a portable, continuous DNA analyzer that may be useful for medical and military applications.

A medium for long-range electron transfer (ET) via its base stacking was suggested as the DNA double helix. Although this issue has been discussed for a long time, Barton and colleagues have proven electrochemically that well-oriented gold electrode DNA films enable long-range electron transfer and that such ET is highly sensitive to base stacking pertubations like mismatches. They found that electroactive intercalators like methylene blue (MB) could be effectively reduced by a fully matched DNA duplex-modified electrode. The existence of only a single mismatch, however, converts the wire-like ET medium into an insulator, totally disrupting the ET between the MB and the electrode. Via cyclic voltammetric or coulometric assays, which form the basis of a rapid DNA mutation screening sensor, such a difference can be easily read. Barton and colleagues also demonstrated that electrocatalysis could improve the sensitivity of this strategy. In solution, the addition of ferricyanide constantly pulls electrons from electrochemically reduced MB, amplifying electron flow through the double helix of DNA. This helps in detecting ~108 molecules of DNA with a 30-μm electrode. They have also developed DNA-based sensors to detect DNA-binding proteins in parallel with DNA detection. Some DNA-binding proteins or enzymes are believed to interact with the base pair stacking of DNA, transforming the double helix of DNA from effective ET wires to insulators. They established a sensitive way to electrically assay a variety of DNA-binding proteins based on the comparable sensing strategy. Crucially, these sensors discriminate successfully against proteins that bind to DNA, but they do not disrupt base stacking. This certainly confirms that the signal cut-off on protein binding is due to the alteration of the ET medium relevant to base stacking.

The future of clinical biosensors

Despite the rapid improvement in the development of biosensors, clinical applications of biosensors are still uncommon, with an exception being the glucose monitor. This is in direct contrast to the critical need for point-of-care testing in small clinics. We assume the specifications below are relevant. First, high sensitivity: Improvement of sensitivity is an ever-lasting priority in the development of biosensors. It is clear that the sensitivity criterion ranges from case to case. For example, because glucose levels are high in the blood, one does not need very high sensitivity for glucose detection. This is basically part of the reason why glucose monitors have been successful. However, in many situations, in order to meet the requirements of molecular diagnostics and pathogen detection, it is very important to establish highly sensitive biosensors with optimum single-molecule detection. Second, high selectivity: In the application of biosensors, this may be a significant barricade. Most of the biosensors mentioned in the literature function very well in laboratories, but in real test samples, series problems can be addressed. As a result, in order to prevent non-specific surface adsorption, it is important to establish novel approaches to surface modification. Third, multiplexing is crucial for saving assay time, which is particularly important for laboratory or clinic assays. It is therefore important to establish arrays of high-density electrodes as well as electrochemical instruments that can conduct a large number of assays simultaneously. Forth, in order to increase portability, it is essential to create miniaturized biosensors, thus satisfying the field and point-of-care test requirements. Fifth, it is appropriate to integrate and highly automate an ideal biosensor. A solution to this goal is offered by current lab-on-a-chip technologies (microfluidics). We can expect all these features to be integrated into successful biosensors in the future, and can easily detect minute targets within a short period of time.

Blueprints for Biochips: Design & Operation

The term “biochip” has taken on several meanings. Any device or component introducing biological materials, either extracted from biological species or synthesized in a laboratory on a solid substrate can be considered to be a biochip in the most generic sense. In practical terms, however, both miniaturizations, usually in microarray format, and the possibility of low-cost mass production are often involved in biochips. The electronic nose or artificial nose chip, the electronic tongue, the Polymerase chain reaction chip, the DNA microarray chip (gene chip), the protein chip and the biochemical lab-on-a-chip are some examples which meet these qualifications. In the gene chip and the protein chip, the most dynamic biochip research has been done.

Much attention has been paid, in particular, to biochips integrating conventional biotechnology with semiconductor processing, micro-electro-mechanical systems (MEMS), optoelectronics and digital signal and image acquisition and processing.

Thousands of genes and their derivatives (i.e., RNA and proteins) in a given living organism are generally assumed to act in a complicated and coordinated manner that creates the mystery of life. Traditional methods in molecular biology, however, typically operate on a “one gene in one experiment” basis, which assumes that the throughput is very limited and it is difficult to achieve the “whole picture” of gene function. A new technology, called the DNA microarray, has gained considerable attention among biologists in the last decades. This technology aims to measure the whole genome on a single chip so that, meanwhile, researchers can get a better picture of the interactions between thousands of genes.

A gene or DNA chip corresponds to a two-dimensional array of small reaction cells (100 x 100 μm each) produced using high-speed robotics on a solid substrate. A silicon wafer, a thin sheet of glass, plastic, or a nylon membrane could be the solid substrate. Trillions of polymeric molecules from a particular sequence of single strand DNA fragments are immobilized in each reaction cell (Figure 5).

Figure 5. A schematic illustration of a gene chip

DNA fragments may be either short (about 20 to 25) base sequences (A, T, G, and C) or longer complementary DNA strands (cDNA). In each cell, the unique sequence of bases (e.g. CTATGC…) is preselected or configured depending on the expected use. The probes are also called recognized sequences of single-strand DNA fragments immobilized on the substrate. Double-strand DNA fragments are formed when unknown fragments of single-strand DNA samples, called the target, react (or hybridize) with the probes on the chip, where the target and the probe are complementary according to the base pairing rule (A paired with T, and G paired with C). The target samples are often labeled with tags, such as fluorescents, dyes, or radio-isotope molecules, to facilitate the diagnosis or analysis of the hybridized chip. Each is labeled with its own distinguishable tag when the targets contain more than one type of sample. This type of DNA microarray chip provides a platform where, based on the size of the array, the unknown target or targets can theoretically be defined with very high speed and high throughput by matching the components involved in the research and development of biochip technology with tens of thousands of different types of probes through hybridization in parallel, and the related technical disciplines are indicated in Figure 6. Fundamentally, biochip technology is interdisciplinary; it is important that scientists and engineers from different disciplines cooperate synergistically to push this novel technology from a lab interest to practical devices and systems.

Figure 6. The components and the associated technical disciplines involved in the R&D of biochip technology

DNA microarray

With regard to the property of the arrayed DNA sequence of known identity, there are two variants of the DNA microarray technology:

Type I: probe cDNA (500~5,000 bases long) is immobilized using robot spotting to a solid surface such as glass and exposed either separately or in a mixture to a set of targets. This strategy, “traditionally” referred to as DNA microarray, is largely known to be developed at Stanford University.

Type II: in situ (on-chip) or by conventional synthesis accompanied by on-chip immobilization, an array of oligonucleotide (20~80-mer oligos) or peptide nucleic acid (PNA) probes is synthesized. The array is exposed to hybridized, labeled sample DNA and determines the identity/abundance of complementary sequences. This method, “historically” named DNA chips, was established at Affymetrix INC., which sells its photolithographically manufactured products under the Genechip trademark. Oligonucleotide-based chips are developed by several companies using alternative in-situ synthesis or depositioning technologies.

Depending on the type of molecule immobilized, biochip is made primarily in two formats. CDNA arrays are also referred to as biochips containing PCR products of 200 base pairs to 2KB size immobilized along the length of the molecule by covalently cross linking to the surface of the array. Alternatively, oligonucleotide probes may either be synthesized in situ on the array, or covalent links to the termini may be fixed by pre-synthesized oligos. Genechip engineering includes several different parts, such as manufacturing, sample preparation and hybridization of the target sequence, hybridization results detection, design of the oligonucleotide probe, and hybridization image analysis, and various applications, as seen in Figure 7.

Figure 7. Several important aspects related to Genechip technology

First, according to a particular target, many relevant gene sequences will be selected from the DNA database (single nucleic polymorphism for a specific genes, differential expression for a given group of genes or mutation identification). By determining the sequence and length of each probe and its exact position on the chip, a series of unique oligonucleotide probes will be designed based on the selected sequences. With the spotting method or on-chip synthesis, the synthesis of the DNA microarray can be carried out. The target genes are usually necessary for fluorescence to be amplified and labeled. Selection of appropriate PCR primes, optimization of amplification, and hybridization conditions will be needed in most cases. For the hybridization outcomes on a gene chip, there are several different detection strategies. A traditional approach is a fluorescent detection. For the treatment of such a large amount obtained from a gene chip, data analysis based on the fluorescent images and database configuration is required. The use of PCR products corresponding to the genes as probe molecules is a common platform for preparing microarrays. Biological sources of cDNA libraries offer an effective template for PCR amplification of the probes. This platform is therefore referred to as cDNA Arrays.

The use of oligonucleotide probes instead of PCR products has several benefits. First, they are typical of similar length and can be created in such a way that they have similar properties of hybridization. Second, they may be configured to hybridize against the specific gene region; the PCR product also allows cross-hybridization between homologous genes disturbing members of the same gene family’s gene expression profiles. Furthermore, the need for tedious PCR amplification of the probe molecules is eliminated by oligonucleotide arrays and decreases the risk of error due to clone handling and contamination during transfer.

Microfluidic chip

In recent decades, microfluidic technology has been rapidly developed and provides multitudinous applications in the life sciences. Thanks to the distinct benefits provided by system miniaturization, the microfluidics revolution arose, including high analytical efficiency, increased sensitivity, improved analytical performance, fast multiplexing parallelization, the ability to manage and process reduced reagent volumes and dramatically reduced instrumental footprints.

Microfluidics could simultaneously offer analytical efficiency and high throughput capability as a miniaturization technology, without the lack of accuracy and automation. Microfluidics technology is not only a powerful tool for the fast screening and study of drug development during the drug application process, but also for its miniaturized devices to lower costs and reagent consumption.

Significant progress has been made in developing drug screening components and systems based on microfluidics over the past few years. For drug screening, different types of microfluidic chips are used to improve screening efficiency and decrease costs. Several common types of chip technology are described in the following paragraphs.

Figure 8. Application of microfluidic chip in drug screening.

Droplet microfluidics – In order to perform experiments in continuous or segmented flow, droplet microfluidic technology utilizes liquid droplets compartmentalized by an immiscible fluid as nanoliter to picoliter separate reaction vessels. Such methods show significant advantages, such as reduced sample usage, improved reaction speed and increased efficiency and reproducibility, handling incredibly small volumes with robust composition control.

Based on the sequential process droplet array technique, droplet microfluidic methods may be used for drug combination screening (Figure 8A), to screen various dosing combinations and administration lengths, and to refine the optimum minimally consumed dosing regimen that is important for combined disease situations.

Organ-on-chip – The detailed regulation of microscale structure and flow enables the precise modeling of the microscale structures of organ tissue to be built. Organs-on-chips are biomimetic systems that are micro-engineered and represent essential functional units of living human organs. The functions of multiple organs and tissues, such as the liver, kidneys, lungs and intestines, have been replicated as in vitro models to date. These systems could be used as in vitro models that enable complex biological processes to be simulated and pharmacologically modulated.

The organ chip simulates the human body’s basic processes, by using a number of cells to create a biomimetic chip with similar physiological functions on the chip’s unique structure, which is comparable to the disease’s actual external environment than the typical single-cell culture model.

In order to replicate the complex microarchitecture of cancerous tissue, a microsystem that allows co-culture of breast tumor spheroids with neighboring cells in a compartmentalized 3D microfluidic system has been established to help create the anti-breast cancer drug screening platform (Figure 8B). For the study of cancer cell migration and anti-cancer drug screening, co-culture of multiple tissues with a microfluidic system could be used.

Other microfluidic chips for drug screening – There are several other technologies applied to microfluidic chips for drug screening, in addition to the above-mentioned existing methods, which extend the ideas of researchers. The most significant and integrated aspect of drug development in most pharmaceutical and several biotechnology industries around the world has been an outstanding HTDS system.

With the use of open-access microfluidic tissue array systems  and cell microarray chips, various concentrations and combinations of drugs can be screened. Various configurations and arrays of small culture chambers may be generated by the different design of the chip. Concentration gradient generators can provide an effective liquid concentration gradient, and these devices have been implemented and combined with microfluidic technologies by several research groups to optimize HTDS systems. The diffusive microfluidic mixers in Figure 8C could also recognize a fully automatic HTDS.

Cell array platforms are built using polydimethylsiloxane (PDMS) material in certain microfluidic channels for drug screening. The structure of the chips, though, is difficult and has some disadvantages, such as expensive silicon molds and biomolecular absorption. As a natural extracellular matrix (ECM), poly (ethylene glycol) diacrylate (PEGDA) hydrogel has identical mechanical properties and water content. PEGDA microfluidic hydrogels have been commonly used for cell encapsulation and are permeable to compounds such as water, biomolecules and chemicals. In order to research the combinatorial treatment effect of two drugs, microfluidic devices made of these types of materials and combined with 3D brain cell culture technologies were used (Figure 8D).

The allure of the microfluidic chip is that to perform various functions, it can have multiple designed structures and can be combined to extend its application range with different devices and testing equipment. However, considerable design, manufacturing and optimization efforts are needed. Each model has unique features of its own. It is used not only for drug screening, but for drug testing as well.

Protein microarray

In the research of proteins, protein microarrays are useful tools in an unbiased, high-throughput manner, as they allow up to thousands of individually purified proteins to be characterized in parallel. This technology’s adaptability has made it possible to be used in a wide range of applications, including the study of proteome-wide molecular interactions, the analysis of post-translational alterations, the discovery of new drug targets, and the evaluation of pathogen-host interactions. In addition, the technology has already been shown to be effective in profiling the specificity of antibodies, as well as in identifying new biomarkers for autoimmune diseases and cancers in particular.

Proteins are complex biomolecules with a large spectrum of structures and functions, and as such, studying them in a high-throughput manner is a challenge. Three primary types of protein microarrays exist: functional, analytical, and reverse phase. Functional protein microarrays are assembled in a high-through-put manner with proteins purified/synthesized, allowing hundreds and even thousands of different proteins to be examined in parallel with their biochemical properties. In order to detect or measure complex biological samples, analytical protein microarrays use affinity reagents immobilized on the array. Finally, complex biological samples immobilized on the array are used by reverse phase protein microarrays which use affinity reagents for identification.

Functional protein microarrays are more capable of identifying weak interactions, more flexible for low-abundance proteins, and more capable of analyzing crude samples such as serum, compared to other methods, such as mass spectrometry. In terms of differences in proteome coverage, protein lengths, and production pipelines, several different types of functional protein microarrays have been produced to date.

Development of the Functional Protein Microarray – The whole set of proteins that can be expressed by a genome is the proteome. Typically, the creation of a purified proteome microarray requires the assembly of a genome-wide set of open reading frames (ORFs) cloned into an expression vector, encoded protein expression in cells, high-throughput individual protein purification, and protein immobilization on a microarray.

Application of Yeast Proteome Microarrays – For the profiling of proteome-wide molecular interactions, functional protein microarrays, especially purified proteome microarrays, are useful and enable detailed, unbiased screening. Researchers have used functional protein microarrays in fundamental research to study protein-protein interactions, protein-lipid interactions, protein-DNA interactions, protein-cell/lysates, small molecule binding, protein-RNA interactions, and PTMs, such as acetylation, SUMOylation, glycosylation, ubiquitylation, phosphorylation, and methylation (Figure 9A-9G). We summarize representative studies in Table I based on the research applications seen in Figure 9.

Figure 9. Application of Functional Protein Microarray

Applications of biochips

The most emerging applications of biochips are included in Table 1.

Biochip in food Biochip detecting genetically modified organisms (gmo’s) in food.
Biochip in diagnostics DNA biochip which revolutionise the way the medical profession performs tests on blood.
Biochip in Tuberculosis epidemic Biochip technology expected to help combat the new variety of drugresistant strains of the disease.
Biochip in cancer Biosensor chip technology provides quick and easy access to critical information regarding DNA damage from cancer-producing compounds and aid in early detection of colon cancer.
Biochip in cancer DNA chips which find genetic differences between people who respond to a drug and those who do not, starting in Phase II, or mid-stage, clinical trials.

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References

  • Adams DA, Brus L, Chidsey CED, et al. 2003. Charge transfer on the nanoscale: current status. J Phys Chem B, 107: 6668-97.
  • Ashley GW, Henise J, Reid R, et al. 2013. Hydrogel drug delivery system with predictable and tunable drug release and degradation rates. Proc. Natl. Acad. Sci. USA, 110: 2318–2323.
  • Bard AJ, Faulkner LR. 2001. Electrochemical Methods. New York: John W Willey & Sons.
  • Benson DE, Conrad DW, de Lorimier RM, et al. 2001. Design of bioelectronic interfaces by exploiting hinge-bending motions in proteins. Science, 293:1641–4.
  • Boon EM, Ceres DM, Drummond TG, et al. 2000. Mutation detection by electrocatalysis at DNA-modified electrodes. Nature Biotech, 18:1096–100.
  • Boon EM, Livingston AL, Chmiel NH, et al. 2003. DNA-mediated charge transport for DNA repair. Proc Natl Acad Sci U S A, 100:12543–7.
  • Boon EM, Salas JE, Barton JK. 2002. An electrical probe of protein-DNA interactions on DNA-modified surfaces. Nat Biotechnol, 20:282-6.
  • Brazill SA, Kim PH, Kuhr WG. 2001. Capillary gel electrophoresis with sinusoidal voltammetric detection: A strategy to allow four-“color” DNA sequencing. Anal Chem, 73:4882–90.
  • Burgstaller P, Girod A, Blind M. 2002. Aptamers as tools for target prioritization and lead identification. Drug Discov Today, 7:1221–8.
  • Choi Y, Hyun E, Seo J, et al. 2015. A microengineered pathophysiological model of early-stage breast cancer. Lab Chip, 15: 3350–3357.
  • Cooper MA, Dultsev FN, Minson T, et al. 2001. Direct and sensitive detection of a human virus by rupture event scanning. Nature Biotechnol, 19:833–7.
  • Dai Z, Yan F, Yu H, et al. 2004. Novel amperometric immunosensor for rapid separation-free immunoassay of carcinoembryonic antigen. J Immuno Methods, 287:13–20.
  • Das, H.K. 2005. “Functional Gernomics using Microarrays Technology.” Text book of Biotechnology, pp .1276-1288, Wiley Dreamtech Publisher.
    Drummond TG, Hill MG, Barton JK. 2003. Electrochemical DNA sensors. Nat Biotechnol, 21:1192–9.
  • Fan C, Plaxco KW, Heeger AJ. 2003. Electrochemical interrogation of conformational changes as a reagentless method for the sequence-specific detection of picomolar DNA. Proc Natl Acad Sci U S A, 100:9134–7.
  • Fan C, Plaxco KW, Heeger AJ. 2005. Biosensors based on binding-modulated donor-acceptor distances. Trends Biotechnol, 23:186–92.
  • Fan Y, Nguyen DT, Akay Y, et al. 2016. Engineering a brain cancer chip for high-throughput drug screening. Sci. Rep., 6: 25062.
  • Fritz J, Cooper EB, Gaudet S, et al. 2002. Electronic detection of DNA by its intrinsic molecular charge. Proc Natl Acad Sci U S A, 99:14142–6.
  • Gao Z, Binyamin G, Kim H-H, et al. 2002. Electrodeposition of redox polymers and co-electrodeposition of enzymes by coordinative crosslinking. Angew Chem Int Ed, 41:810–13.
  • Gaylord BS, Heeger AJ, Bazan GC. 2002. DNA detection using watersoluble conjugated polymers and peptide nucleic acid probes. Proc Nat Acad Sci U S A, 99:10954.
  • Griffiths AD, Tawfik DS. 2000. Man-made enzymes – from design to in vitro compartmentalisation. Curr Opin Biotech, 11:338–53.
  • Heeger AJ. 2000. Nobel Lecture: Semiconducting and Metallic polymers: The fourth generation of polymeric materials [online]. URL: http:// wwwnobelse.
  • Hook F, Ray A, Norden B, et al. 2001. Characterization of PNA and DNA immobilization and subsequent hybridization with DNA using acoustic- shear-wave attenuation measurements. Langmuir, 17:8305–12.
  • Hsiung LC, Chiang CL, Wang CH, et al. 2011. Dielectrophoresis-based cellular microarray chip for anticancer drug screening in perfusion microenvironments. Lab Chip, 11: 2333–2342.
  • Li Z, Su W, Zhu Y, et al. 2017. Drug absorption related nephrotoxicity assessment on an intestine-kidney chip. Biomicrofluidics, 11: 034114.
    Lin D, Li P, Lin J, et al. 2017. Orthogonal screening of anticancer drugs using an open-access microfluidic tissue array system. Anal. Chem., 89: 11976–11984.
  • Liu J, Zhang Y, Jiang M, et al. 2017. Electrochemical microfluidic chip based on molecular imprinting technique applied for therapeutic drug monitoring. Biosens. Bioelectron., 91: 714–720.
  • Moore CD, Ajala O.Z, Zhu H. 2016. Applications in high-content functional protein microarrays. Curr. Opin. Chem. Biol., 30: 21–27.
  • Palecek E, Jelen F. 2002. Electrochemistry of nucleic acids and development of DNA sensors. Crit Rev Anal Chem, 32:261–70.
  • Palecek E. 2004. Surface-attached molecular beacons light the way for DNA sequencing. Trends Biotechnol, 22:55–8.
  • Park SJ, Taton TA and Mirkin CA. 2002. Array-based electrical detection of DNA with nanoparticle probes. Science, 295:1503–6.
  • Patolsky F, Lichtenstein A, Willner I. 2001. Detection of single-base DNA mutations by enzyme-amplified electronic transduction. Nature Biotech, 19:253–7.
  • Patolsky F, Weizmann Y, Wilner I. 2004. Long-range electrical contacting of redox enzymes by SWCNT connectors. Angew Chem Int Ed, 43:2113–17.
  • S. Mi, Z. Du, Y. Xu, et al. 2016. Microfluidic co-culture system for cancer migratory analysis and anti-metastatic drugs screening. Sci. Rep., 6: 35544.
  • Schuster GB. 2000. Long-range charge transfer in DNA: transient structural distortions control the distance dependence. Acc Chem Res, 33:253-60. Sullivan CKO. 2002. Aptasensors–the future of biosensing? Anal Bioanal Chem, 372:44–8.
  • Stone HA, Stroock AD, Ajdari A. 2004. Engineering flows in small devices: microfluidics toward a lab-on-a-chip. Annu. Rev. Fluid Mech., 36: 381–411.
    Sugiura S, Hattori K, Kanamori T. 2010. Microfluidic serial dilution cell-based assay for analyzing drug dose response over a wide concentration range. Anal. Chem., 82: 8278–8282.
  • Taton TA, Mirkin CA, Letsinger RL. 2000. Scanometric DNA array detection with nanoparticle probes. Science, 289:1757–60.
  • Thorp HH. 2003. Reagentless detection of DNA sequences on chemically modified electrodes. Trends Biotechnol, 21:522–4.
  • Umek RM, Lin SW, Vielmetter J, et al. 2001. Electronic detection of nucleic acids–A versatile platform for molecular diagnostics. J Mol Diag, 3:74–84.
  • Van Hove AH, Antonienko E, Burke K, et al. 2015. Temporally tunable, enzymatically responsive delivery of proangiogenic peptides from poly (ethylene glycol) hydrogels. Adv. Healthc. Mater., 4: 2002–2011.
  • Whitesides GM, Grzybowski B. 2002. Self-assembly at all scales. Science, 295:2418–21.
  • Willner I. 2002. Biomaterials for sensors, fuel cells, and circuitry. Science, 298:2407.
  • Wosnick JH, Swager TM. 2000. Molecular photonic and electronic circuitry for ultra-sensitive chemical sensors. Curr Opin Chem Biol, 4:715–20.
  • Xiao Y, Patolsky F, Katz E, et al. 2003. Plugging into enzymes: nanowiring of redox enzymes by a gold nanoparticle. Science, 299:1877–81.
  • Xu H, Wu H, Huang F, et al. 2005. Magnetically assisted DNA assays: High selectivity using conjugated polymers for amplified fluorescent transduction. Nucleic Acids Res, 33:e83.
  • Yu CJ, Wan YJ, Yowanto H, et al. 2001. Electronic detection of single-base mismatches in DNA with ferrocene-modified probes. J Am Chem Soc, 123:11155–61.
  • Yu X, Kim SN, Papadimitrakopoulos F, et al. 2005. Protein immunosen- sor using single-wall carbon nanotube forests with electrochemical detection of enzyme labels. Mol Biosyst, 1:70–8.
  • Adams DA, Brus L, Chidsey CED, et al. 2003. Charge transfer on the nanoscale: current status. J Phys Chem B, 107: 6668-97.
  • Ashley GW, Henise J, Reid R, et al. 2013. Hydrogel drug delivery system with predictable and tunable drug release and degradation rates. Proc. Natl. Acad. Sci. USA, 110: 2318–2323.
  • Bard AJ, Faulkner LR. 2001. Electrochemical Methods. New York: John W Willey & Sons.
  • Benson DE, Conrad DW, de Lorimier RM, et al. 2001. Design of bioelectronic interfaces by exploiting hinge-bending motions in proteins. Science, 293:1641–4.
  • Boon EM, Ceres DM, Drummond TG, et al. 2000. Mutation detection by electrocatalysis at DNA-modified electrodes. Nature Biotech, 18:1096–100.
  • Boon EM, Livingston AL, Chmiel NH, et al. 2003. DNA-mediated charge transport for DNA repair. Proc Natl Acad Sci U S A, 100:12543–7.
  • Boon EM, Salas JE, Barton JK. 2002. An electrical probe of protein-DNA interactions on DNA-modified surfaces. Nat Biotechnol, 20:282-6.
  • Brazill SA, Kim PH, Kuhr WG. 2001. Capillary gel electrophoresis with sinusoidal voltammetric detection: A strategy to allow four-“color” DNA sequencing. Anal Chem, 73:4882–90.
  • Burgstaller P, Girod A, Blind M. 2002. Aptamers as tools for target prioritization and lead identification. Drug Discov Today, 7:1221–8.
  • Choi Y, Hyun E, Seo J, et al. 2015. A microengineered pathophysiological model of early-stage breast cancer. Lab Chip, 15: 3350–3357.
  • Cooper MA, Dultsev FN, Minson T, et al. 2001. Direct and sensitive detection of a human virus by rupture event scanning. Nature Biotechnol, 19:833–7.
  • Dai Z, Yan F, Yu H, et al. 2004. Novel amperometric immunosensor for rapid separation-free immunoassay of carcinoembryonic antigen. J Immuno Methods, 287:13–20.
  • Das, H.K. 2005. “Functional Gernomics using Microarrays Technology.” Text book of Biotechnology, pp .1276-1288, Wiley Dreamtech Publisher.
    Drummond TG, Hill MG, Barton JK. 2003. Electrochemical DNA sensors. Nat Biotechnol, 21:1192–9.
  • Fan C, Plaxco KW, Heeger AJ. 2003. Electrochemical interrogation of conformational changes as a reagentless method for the sequence-specific detection of picomolar DNA. Proc Natl Acad Sci U S A, 100:9134–7.
  • Fan C, Plaxco KW, Heeger AJ. 2005. Biosensors based on binding-modulated donor-acceptor distances. Trends Biotechnol, 23:186–92.
  • Fan Y, Nguyen DT, Akay Y, et al. 2016. Engineering a brain cancer chip for high-throughput drug screening. Sci. Rep., 6: 25062.
  • Fritz J, Cooper EB, Gaudet S, et al. 2002. Electronic detection of DNA by its intrinsic molecular charge. Proc Natl Acad Sci U S A, 99:14142–6.
  • Gao Z, Binyamin G, Kim H-H, et al. 2002. Electrodeposition of redox polymers and co-electrodeposition of enzymes by coordinative crosslinking. Angew Chem Int Ed, 41:810–13.
  • Gaylord BS, Heeger AJ, Bazan GC. 2002. DNA detection using watersoluble conjugated polymers and peptide nucleic acid probes. Proc Nat Acad Sci U S A, 99:10954.
  • Griffiths AD, Tawfik DS. 2000. Man-made enzymes – from design to in vitro compartmentalisation. Curr Opin Biotech, 11:338–53.
  • Heeger AJ. 2000. Nobel Lecture: Semiconducting and Metallic polymers: The fourth generation of polymeric materials [online]. URL: http:// wwwnobelse.
  • Hook F, Ray A, Norden B, et al. 2001. Characterization of PNA and DNA immobilization and subsequent hybridization with DNA using acoustic- shear-wave attenuation measurements. Langmuir, 17:8305–12.
  • Hsiung LC, Chiang CL, Wang CH, et al. 2011. Dielectrophoresis-based cellular microarray chip for anticancer drug screening in perfusion microenvironments. Lab Chip, 11: 2333–2342.
  • Li Z, Su W, Zhu Y, et al. 2017. Drug absorption related nephrotoxicity assessment on an intestine-kidney chip. Biomicrofluidics, 11: 034114.
    Lin D, Li P, Lin J, et al. 2017. Orthogonal screening of anticancer drugs using an open-access microfluidic tissue array system. Anal. Chem., 89: 11976–11984.
  • Liu J, Zhang Y, Jiang M, et al. 2017. Electrochemical microfluidic chip based on molecular imprinting technique applied for therapeutic drug monitoring. Biosens. Bioelectron., 91: 714–720.
  • Moore CD, Ajala O.Z, Zhu H. 2016. Applications in high-content functional protein microarrays. Curr. Opin. Chem. Biol., 30: 21–27.
  • Palecek E, Jelen F. 2002. Electrochemistry of nucleic acids and development of DNA sensors. Crit Rev Anal Chem, 32:261–70.
  • Palecek E. 2004. Surface-attached molecular beacons light the way for DNA sequencing. Trends Biotechnol, 22:55–8.
  • Park SJ, Taton TA and Mirkin CA. 2002. Array-based electrical detection of DNA with nanoparticle probes. Science, 295:1503–6.
  • Patolsky F, Lichtenstein A, Willner I. 2001. Detection of single-base DNA mutations by enzyme-amplified electronic transduction. Nature Biotech, 19:253–7.
  • Patolsky F, Weizmann Y, Wilner I. 2004. Long-range electrical contacting of redox enzymes by SWCNT connectors. Angew Chem Int Ed, 43:2113–17.
  • S. Mi, Z. Du, Y. Xu, et al. 2016. Microfluidic co-culture system for cancer migratory analysis and anti-metastatic drugs screening. Sci. Rep., 6: 35544.
  • Schuster GB. 2000. Long-range charge transfer in DNA: transient structural distortions control the distance dependence. Acc Chem Res, 33:253-60. Sullivan CKO. 2002. Aptasensors–the future of biosensing? Anal Bioanal Chem, 372:44–8.
  • Stone HA, Stroock AD, Ajdari A. 2004. Engineering flows in small devices: microfluidics toward a lab-on-a-chip. Annu. Rev. Fluid Mech., 36: 381–411.
    Sugiura S, Hattori K, Kanamori T. 2010. Microfluidic serial dilution cell-based assay for analyzing drug dose response over a wide concentration range. Anal. Chem., 82: 8278–8282.
  • Taton TA, Mirkin CA, Letsinger RL. 2000. Scanometric DNA array detection with nanoparticle probes. Science, 289:1757–60.
  • Thorp HH. 2003. Reagentless detection of DNA sequences on chemically modified electrodes. Trends Biotechnol, 21:522–4.
  • Umek RM, Lin SW, Vielmetter J, et al. 2001. Electronic detection of nucleic acids–A versatile platform for molecular diagnostics. J Mol Diag, 3:74–84.
  • Van Hove AH, Antonienko E, Burke K, et al. 2015. Temporally tunable, enzymatically responsive delivery of proangiogenic peptides from poly (ethylene glycol) hydrogels. Adv. Healthc. Mater., 4: 2002–2011.
  • Whitesides GM, Grzybowski B. 2002. Self-assembly at all scales. Science, 295:2418–21.
  • Willner I. 2002. Biomaterials for sensors, fuel cells, and circuitry. Science, 298:2407.
  • Wosnick JH, Swager TM. 2000. Molecular photonic and electronic circuitry for ultra-sensitive chemical sensors. Curr Opin Chem Biol, 4:715–20.
  • Xiao Y, Patolsky F, Katz E, et al. 2003. Plugging into enzymes: nanowiring of redox enzymes by a gold nanoparticle. Science, 299:1877–81.
  • Xu H, Wu H, Huang F, et al. 2005. Magnetically assisted DNA assays: High selectivity using conjugated polymers for amplified fluorescent transduction. Nucleic Acids Res, 33:e83.
  • Yu CJ, Wan YJ, Yowanto H, et al. 2001. Electronic detection of single-base mismatches in DNA with ferrocene-modified probes. J Am Chem Soc, 123:11155–61.
  • Yu X, Kim SN, Papadimitrakopoulos F, et al. 2005. Protein immunosen- sor using single-wall carbon nanotube forests with electrochemical detection of enzyme labels. Mol Biosyst, 1:70–8.

Biosensors & Biochips for Sustainable Future

ADVANCE   L E V E L

The field of synthetic biology has exploded over the past decade, having a major influence on fields such as metabolic engineering, protein engineering, digital biology, and whole-genome engineering.

Contents

 

Biosensors & Biochips Technologies: Contribution to the Future Sustainable Life

The field of synthetic biology has exploded over the past decade, having a major influence on fields such as metabolic engineering, protein engineering, digital biology, and whole-genome engineering. In the framework of iterative “design-build-test” development cycles, a significant portion of synthetic biology innovation has taken place. In the field of synthetic biology, progress can be associated with innovations in each of the processes of “design”, “build” and “test”. For example, there has been a major push to standardize elements within synthetic biology, with significant attention being paid to modularity and “plug and play” components. This modularization, along with the accelerated progress in systems biology, has allowed the “design” stage to become less time-consuming and less reliant on advanced knowledge. In recent years, the cost of DNA sequencing and synthesis has also decreased dramatically, allowing large constructs to be synthesized cheaply. In the ‘build’ phase, this has facilitated a rapid improvement, helping researchers to investigate a larger percentage of the space of the biological solution. Finally, within the synthetic biology “test” phase, high-throughput screening has also become a focal point. The increased “design” and “build” potential has contributed to an increased demand for success in the assessment of the plethora of new designs. In turn, this was done by incorporating robots and high-throughput analytics into the laboratory setting, in which new models can be evaluated to a level that is not achievable for human researchers.

Biosensors represent a groundbreaking emerging technology for high-throughput screening that can be implemented. Most precisely, they are classified as an analytical tool consisting of biological components used to detect and generate a signal for the presence of a target ligand. Synthetic biology is at the forefront of biosensors, both as a tool for high-throughput screening, but also as the direct result of developments within the field of synthetic biology itself. In addition, because of the unparalleled specificity and sensitivity that biological parts provide relative to conventional analytical methods, biosensors have gained expanded interest as alternatives to traditional analytics.

The design and construction of biosensors is a multidisciplinary endeavour and can include expertise in areas such as protein engineering, molecular biology, affinity chemistry, molecular dynamics of nucleic acid, materials sciences, and nanotechnology. Biosensors interface with a target ligand at their most simple stage, undergo some type of modification, and output a signal. There is a great variety of potential configurations in all the parts of this process. Target ligands range from single atoms such as calcium, to entire proteins such as thrombin, all the way through. Processes as varied as enzymatic activity, fluorescence, electrical current generation, and transcriptional activity include output signals. The mechanisms that transduce ligand recognition into functional signals are just as diverse.

In the field of analytics, biosensors represent a significant step forward. In order to move analytics away from purely physics- or chemistry-based frameworks, the integration of biological components in sensory diagnostics has begun. This has allowed analytical functions that are not well adapted to conventional methods to conduct a vast diversity and specificity of biological components. The theoretical and demonstrated biosensor applications cover a significant range of human society and activity. Biosensor applications are grouped into three broad categories, depending on their measurement scale.

  • Group Diagnostics: Environmental, Agricultural, and Industrial Applications
  • Point-of-Use Diagnostics: Medical, and Security Applications
  • Single-Cell Diagnostics: Metabolic Engineering, and Synthetic Biology Applications

Biosensors & biochips: advances in medical diagnostics

Biosensors consist of a biocatalyst that can recognize a biological element and a transducer that can turn the biocatalyst and the biological element combination occurrence into a measurable parameter.

The biocatalyst may be biomolecules such as enzymes, DNA, RNA, metabolites, cells, oligonucleotides, etc., and electrochemical, calorimetric, optical, acoustic, piezoelectric, etc. transducers. Biosensors using immobilized cells, enzymes and nucleic acids have come into the field in recent years in disease diagnostics. For engineering disease diagnostic biosensors, nanobiosensors utilizing the ultra-small size and unique properties have also been applied. The use of biosensors can quickly determine the health status, the onset and progression of the disease and, with the assistance of a multidisciplinary combination of chemistry, medical science and nanotechnology, can help to prepare treatment for many diseases. The devices are cost-effective, highly responsive, fast, user-friendly, and can be manufactured for human use in bulk. Numerous biosensors for the diagnosis of three major diseases, such as diabetes, cardiovascular disease and cancer, are the most developed ones.

Such biosensors, coined by Cammann, are analytical instruments that transform an electrical signal into a biological response. Biosensors can usually be highly precise and should be recyclable and irrespective of physical limitations such as pH, temperature. Practical approach to the design of a biosensor requires manufacturing, immobilization, transduction devices that offer multidisciplinary research engineering in both chemistry and biology.

Based on their working mechanism the diagnostic biosensors are divided into four major groups:

  1. Enzyme-based biocatalytic biosensors.
  2. Bioaffinity group, i.e. antibody, antigen and nucleic acid presence.
  3. Microbes, i.e., microorganism-containing biosensors.
  4. Nanosensors, i.e. active nanoparticle sensors that typically increase sensitivity and specificity for early disease detection.

These various types of biosensors help hormone levels, drugs, toxins, contaminants, heavy metals, pesticides, etc. to be identified with significant specificity.

Biosensors are tools that commonly estimate biological marker levels or any chemical reaction by creating signals that are primarily associated with an analyte’s concentration in the chemical reaction. Typically, such biosensors help monitor diseases, drug discovery, pollutant detection, bacteria-causing disease detection, and markers that usually indicate diseased conditions, such as body fluids (saliva, blood, urine, sweat, etc.). A typical biosensor is shown in Figure 1.

Figure 1. Schematic depiction of biosensor

A typical biosensor is composed of:

  1. Analyte: A substance of interest, such as glucose for diabetes, that needs to be established.
  2. Bioreceptor: A bioreceptor for enzymes may be a molecule which recognizes the analyte.
  3. Transducer: Normally, a bio recognition event is converted into a detectable signal, known as signalization.
  4. Electronics: In display form, it typically processes the transduced signal.
  5. Display: Typically, the liquid crystal display results in a user-friendly manner in combination with hardware and software for biosensor generation.

There are several biosensor applications that have been introduced in different areas, such as medical science, the marine sector, the food industry, etc., and these biosensors are often programmed for improved sensitivity and linearity compared to conventional methods. However, the application of biosensors is growing increasingly in the field of medical science.

Glucose biosensors in diabetic management

Blood glucose monitoring has become a valuable tool in the management of diabetes and daily blood glucose levels are typically maintained by consulting clinicians who have developed a series of blood glucose sensors. Diabetes mellitus is the largest prevailing carbohydrate metabolism endocrine disorder with more morbidity and mortality in developing countries. Multiple tests are usual in diabetic patients for the investigation and monitoring of diabetic markers. The key diagnosis criteria for diabetes are the level of blood glucose, which includes diabetic patients’ self-monitoring of glucose levels. Studies have shown that microvascular (nephropathy, neuropathy, and retinopathy) and macrovascular (coronary artery disease and stroke) complications can be improved by controlling the level of blood glucose in the normal range. Blood glucose is typically observed in healthy individuals in the range of 4.9-6.9 mM and can increase in diabetic patients up to 40 mM after glucose intake. Although different kinds of glucose sensors are commercially available, the third generation of glucose biosensors is shown in Figure 2 as an example.

Figure 2. Third generation of glucose biosensor

Cardiovascular disease detection using biosensors

The number of deaths caused globally by cardiovascular disease (CVD) is significant and more people die of CVD than by any other disease. By 2015, about 17.7 million people had died from CVD, representing a total of 31 % of all global deaths. 7.4 million of these were due to coronary heart disease and 6.7 million were due to stroke. By way of medication and therapy, a person with CVD needs earlier detection and management. The current CVD detection strategy relies on the traditional method, which is usually based on testing that can take many hours or even days. The WHO sets these diagnostic criteria, under which patients should follow at least one of the conditions, such as changes in the diagnostic electrocardiogram (ECG), elevation of biochemical markers in their blood samples, and characteristic chest pain. ECG is an important parameter for therapy management, but ECG is a poor diagnostic test in the case of CVD because half of CVD patients have a normal cardiogram, making it more difficult to diagnose this medical condition. Biosensor will aid in rapid diagnosis, providing excellent health care and reducing the delay time for the distribution of the results, which is immense stress for the patients.

Biosensor for detection of cancer

Cancer is one of the most lethal diseases, and several researchers have recently developed biosensors for early cancer detection. Most cancers are typically diagnosed by MRI, ultrasound or biopsy methods that rely on the physical properties and presence of the tumor and identify either advanced or invasive instruments. The variations in gene sequences, i.e. mutations, primarily cause cancer and thus require early diagnosis before the disease progresses. Early cancer detection makes treatment faster and more successful, opening up a biosensor platform for the detection of early cancer stages. Many experts assume that in the case of cancer, early detection could be possible because abnormalities in chemical and genetic composition may be identified long before the disease begins. Uncontrolled and irregular cell growth, commonly believed to be cancer, occurs due to the accumulation of unique genetic mutations and epigenetic defects. The tumor cells are shown to be resistant to apoptosis and the body’s anti-growth defense mechanism. If it progresses and begins to expand to other body organs and systems, i.e. metastasize stage, the cancer becomes incurable. Oncogene stimulation and reducing the function of tumor suppressor genes (TSGs) are the two most important tumorigenesis mechanisms. Due to mutation or replication of normal gene (proto-oncogene), activation of oncogene takes place, which plays key roles including, control of cell growth, proliferation, and/or differentiation. Such genetic mutation guides the gene to produce an excess quantity of its gene product, resulting in disregulation of cell division, cell growth and tumor establishment. Many oncogenes have been considered as promising cancer biomarkers for growth factor receptors. In ~ 33 % of all breast cancers, the human epidermal growth factor receptor Her-2 is intensified, and cancers with strengthened Her-2 seem to develop and increase more rapidly. Awareness of Her-2 status is therefore essential in concluding the possible medication course. Trastuzumab is now a typical adjuvant therapy for patients with this type of amplified gene expression, a recombinant humanized monoclonal antibody targeted at Her-2 as a straight-forward treatment for breast cancer. TSGs are related to the control of insufficient cell growth and proliferation by minimizing or preventing the division of cells. Retinoblastoma protein (Rb), BRCA1/2, and p53 are three of the well-studied TSGs in cancer. Rb is a master cell division regulator, and Rb mutation plays a significant role in various cancers. The most common causes of inactivation of the Rb1 gene are point mutations and deletions. BRCA1 is a DNA repair enzyme that is associated with newly replicated DNA ‘proofreading’ for fidelity and to search for any mutations. Until the cell divides, DNA repair enzymes normally work to excise replication errors. BRCA1 gene mutations are responsible for 50% of hereditary breast cancers and 80-90% of hereditary breast and ovarian cancers. Lastly, a main regulator of apoptosis or programmed cell death is the p53 protein. In the brain, breast, colon, lung, hepatocellular carcinomas, and leukaemia, p53 mutations are found. Another significant involvement with p53 loss is that it leads to the mechanism of resistance of chemotherapy drugs. The improvement of biosensors that can detect the existence of p53, Rb, and BRCA1 mutations is highly warranted and can enable us to evaluate the susceptibility of early cancer with detailed prognosis and treatment regimes.

Biochip in diagnostics

The DNA biochip opens up a new genetics-based field of diagnostics. The way the medical profession performs blood testing could be revolutionized by a newly developed DNA biochips. They are virtually immediate with the matchbox-sized biochip instead of a patient having to wait several days for results from a laboratory. And with no sacrifice of accuracy, it requires less blood. The DNA biochip reduces the need for radioactive labels used for detection, in addition to time savings. For technicians and laboratory workers handling samples and performing tests, this significantly decreases costs and future health effects. It also lowers disposal costs because, according to strict regulations, chemically labelled blood must be handled.

A biosensor must be highly sensitive and able to differentiate between, for example, bacteria, viruses or other chemical or biological species to be useful for detecting compounds in a real-life sample. According to Vo-Dinh, who clarified that the biochip mimics the sophisticated recognition capabilities of a living system, DNA biochips do that. The DNA biochip is a gene probe-based biosensor, as opposed to other biosensors based on enzyme and antibody probes. Gene probe-based biosensors provide exceptional selectivity and sensitivity, making them valuable tools for diagnosing genetic diseases and infectious species.

Biochip in Tuberculosis epidemic

The development of new biochip technologies by Russian and American scientists could bring some hope of halting the global resurgence of tuberculosis. Established by the U.S. Department of Energy’s Argonne National Laboratory and the Russian Academy of Sciences’ W. A. Englehardt Institute of Molecular Biology (Moscow), the technology is intended to help combat the current variety of drug-resistant strains of the disease.

The World Health Organization reports that tuberculosis kills more young people and adults, including AIDS and malaria combined, than any other infectious disease. The biggest challenge of the ongoing tuberculosis epidemic is that the disease can be caused by several different bacterial species, and each one is resistant to various drugs. The critical element in controlling the disease is to define the strain that affects a given patient and to determine the best antibiotic for combating that strain. To differentiate between numerous tuberculosis strains, Argonne intends to use biochip technology in research. Testing on segments of genetic material removed from tuberculosis bacteria would initially be carried out. Biochips are designed to simultaneously conduct a number of biochemical reactions and have been found to perform satisfactorily in laboratory testing. Since the detection of specific tuberculosis strains takes weeks or months, patients are frequently prescribed several antibiotics simultaneously.

Biochip in cancer

The biosensor chip technology also provides fast and simple access to crucial information about cancer-producing compound DNA damage, moving researchers a step closer in the fight against cancer. Unlike traditional methods of biosensing, a laser-based, high-resolution and low-temperature fluorescence method offers a precise fingerprint of the molecule. It is possible that its ease of use encourages the replacement of invasive endoscopic procedures and helps to detect colon cancer early on.

Biosensors & Biochips applied in food and agriculture

The current food production faces immense challenges from the increasing human population, the maintenance of clean resources and food quality, and the protection of the environment and climate. Food sustainability is mainly a cooperative effort that results in the development of technology funded by both governments and companies. Several attempts have been supported to overcome challenges and improve the drivers in food production. Via their applications, biosensors and biosensing technologies are widely used to solve the major challenges of food production and its sustainability. As a result, there is a rising need for biosensing technology in the area of food sustainability. A technological system combining several technologies is defined by microfluidics. Nanomaterials, with its biosensing technology, is known to be the most innovative tool strongly associated with world populations in dealing with health, energy, and environmental issues. The need for point of care (POC) technology in this area focuses on analytical tools that are fast, simple, precise, compact, and low-cost.

For our existence and lives, food with its production industry is essential; and its sustainability is essential in continuous human growth on the planet. Current food production is facing immense difficulties from increasing human population, maintaining clean resources and food quality, and protecting environment and climate. Some of these issues stem from food production itself; others stem from other food production-related industries. Food recalls, for example, trigger major damage to food brands’ credibility and prestige, with an estimate of $15 million per incident over the last few years. 48 million sick cases are responsible for 3000 fatalities annually due to foodborne illnesses.

Food safety is largely a cooperative effort arising from both governments and companies in technology development. In order to pose new challenges in food safety issues, information technologies such as blockchain technology can accelerate communication between food quality, media and consumers. Five challenges can be summarized as the main challenges in the sustainability of food production: the production challenge of food safety and security; the quality challenge of food diversity and quality; the economic challenge in the leading food system, including its packaging and supply chain; the environmental challenge, including the processing of food waste; and the engineering challenge in the creation and generation of novel food.

Basically, a biosensor is an analytical instrument used to measure a sample’s molecule of interest (target). In general, a bio-recognition factor (aptamer, antibody, enzyme, etc.) that is unique to the target is used. A physiochemical or biological signal is elicited by molecular recognition events between the recognition element and the target compound, which is transformed into a measurable quantity by the transducer. Signals are shown in either optical (colorimetric, fluorescence, chemiluminescence and plasmon surface resonance) or electrical (voltammetry, impedance and capacitance) or any other chosen format (Figure 3).

Figure 3. Classification of biosensors based on transducer and bio-recognition elements used in food analysis

As one of the primary objectives of food analysis, food safety is a major health issue in both animal and human lives. The advancement of food safety analytical technology means that it thrives in line with the rising interest in and emphasis on food supply safety issues. In food safety analysis, traditional approaches are labour-intensive, time-consuming, and need trained technicians. The application of microfluidics in food safety analysis provides fresh insight about how to detect foodborne toxins, allergens, pathogens, hazardous substances, heavy metals, and other contaminants effectively and rapidly. Microfluidics’ features, such as it miniaturize-capability, compact and reducible quantities of samples and reagents, make it a perfect technology for the development of food sustainability. Complex food matrix preparation and difficult manufacturing steps are the current challenges in the application of microfluidics to food sustainability. These challenges can be addressed by leveraging physical properties dependent on specific test targets, designing complex real food analysis microfluidic platforms, and incorporating into microfluidic systems biomolecules such as food proteins and DNA.

Nanomaterials in biosensing technology

With its biosensing technology, nanomaterials are the most promising tool in dealing with health, energy and environmental problems associated with population in the world. Particles smaller than 100 nm in at least one size dimension are known as nanomaterials. These nanomaterials are biocomposite polymers based on metal, metal oxide and carbon, and different types of nanoparticles have been established, such as magnetic iron, aluminum, gold, silver, copper, silica, zinc, zinc oxide, cerium oxide and titanium dioxide nanoparticles, and single/multiple walled carbon nanotubes (CNTs). Nanotechnology and its agricultural development have been greatly extended in different fields. These fields include food production, crop protection, detection of pathogens and toxins, purification of water, food packaging, disposal of wastewater, and environmental remediation. Improving the productivity and performance of applications is the priority of these agricultural fields.

In the field of food safety and protection, biosensing technologies have been developed for nutrient and quality detection, detection of pathogens and detection of toxins, as listed below.

Nutrient and quality detection

Food protection measures can be split down into two categories: post-harvest loss and food biosecurity. Food biosecurity means food contamination and degradation, which is addressed in the later sections, by environmental, political, unfair economic gain, warfare, or exacting revenge. Post-harvest loss, on the other hand, suggests the nutrients and edible conditions in food that need to be maintained between the harvest period and the moment of consumption by technologies. Since time differs from minutes to years, in maintaining and reducing losses, technologies focusing on reducing post-harvest losses are important.

To maintain food quality and to avoid post-harvest losses, new technology such as biosensing can be used. Biosensors have been developed, for example, to detect and analyse quantities of sweeteners in foods that can be used to detect both natural and artificial sweeteners. Sweeteners are widely used in food production and processing, but they have recently been identified in humans as causing health problems. A multi-channel biosensor has been developed to use electro-physiological sensing from taste epithelia to detect and analyse both natural and artificial sweeteners. To detect long-term signals from sucrose, glucose, cyclamate, and saccharin, respectively, the signals are studied through spatiotemporal techniques. The biosensor can distinguish between different concentrations with dose-dependent increased responses of the taste epithelium from different sweeteners. It can also distinguish between two natural sweeteners: sucrose and glucose, with two signal patterns. For glucose, the detection range is 50-150 mM, and for saccharin, 5-15 mM.

Detection of pathogens

Due to their reduced format, biosensors targeting pathogen detection such as bacteria (Table 1) and fungi (Table 2) started more than two decades ago; one device to address multiple problems, and a multi-panel signal detection. The ligand motif is a crucial element in the biosensor design for pathogen detection since it determines the sensitivity and efficiency of the device. The aim is to establish a fast, specific, and sensitive platform to detect in food samples the presence or absence of pathogens. It has been discovered that there is no ideal ligand, and various ligands have different advantages. The combination of bioreceptors to detect a large variety of microbes in different samples poses current challenges in pathogen biosensor detection; new synthetic ligand designs such as aptamers, small molecules, and peptides; and the incorporation of different ligands into a portable device to achieve rapid, effective, and low-cost detection.

Table 1. Conditions for numbers of bacteria grown in milk

Temperature °C 24 h 48 h 96 h 168 h
0 2100 2100 1850 1400
4 2500 3600 218,000 4,200,000
8 3100 12,000 1,480,000
10 11,600 540,000
15 180,000 28,000,000
30 1,400,000,000

Table 2. Temperature and water activity requirements for fungal growth

Species Minimum Optimum Maximum Minimum Optimum
Aspergillus ruber 5 24 38 0.72 0.93
A. amstelodami 10 30 42 0.70 0.94
A. flavus 12 35 45 0.80 0.99
A. fuminatus 12 40 52 0.83 0.99
A. niger 10 35 45 0.77 0.99
Penicillium martensii 5 24 32 0.90 0.99

Detection of toxins

The mainstream of development in food safety is electrochemical biosensors for rapid detection and assessment of food toxins. Numerous platforms have been developed to allow customized and individualized devices to meet particular environmental and organizational requirements and to reach the nM to fM detection limit levels. For example, to encourage unique binding profiles, bioreceptor arrays address individual electrodes functionalized with different bioreceptors with binding targets. In addition to electrochemical biosensing, toxin and chemical detection in food production have been applied to other biosensors such as optic and piezoelectric sensing (Figure 4). In order to sense toxins, fluorescent nanoparticles have been produced in foods and bodies, including on-surface, inter- and intra-cellular foods.

Figure 4. Predominant food contaminants and the target analytes in the food manufacturing industries

Toxin extraction from complicated food samples is one of the main obstacles in creating a fully automated toxin detector. To automatically assess their harmful levels from food and water samples, potential systems are expected to extract, process, and measure toxins. In identifying, discriminating, and quantifying chemical toxins in food matrices, sophisticated separation strategies have been coupled with SERS. In addition, even though they are typically in lower amounts, chemical contaminants from food processing can be a challenge. Lower stability, selectivity and sensitivity are another challenge in food toxin detection, where MIPs can be a solution to provide stable and low-cost alternatives.

Heavy metals like Ag+, As3+, Cd2+, Hg2+, Pb2+, and Zn2+ are known as chemical pollutants that form stable states of oxidation and interfere with metabolic pathways, resulting in health problems. Aptamer and DNA-based biosensors can detect heavy metals at both nanoscale and very large-scale levels, which are appropriate for food safety screening and monitoring. In order to detect arsenate in food, a heavy metal detecting biosensor is based on genetically modified bacterial cells and a green, fluorescent signal amplifier. With a detection range of 5-140 μg/L of arsenic, its arsenic detection lasts just one hour and can be integrated with optical power output for its future biosensing optical fibre. Other biosensing technologies like aptamers, nanoparticles and graphene electrodes have been successfully applied to the identification and evaluation of arsenic, with the potential to be produced as fast, simple, easy-to-use, and low-cost devices.

Nanotechnology has been adapted to two separate fields of agri-food pesticides: as a pesticide delivery vector for pesticide management and as a trace-amount detector for pesticides. In the first field, nanoparticles are able to slowly modify pesticides to target insect pests, which helps prevent groundwater and topsoil pollution, reduce pesticide levels and improve efficiency. In the second field, bio- or biomimetic-based nanotechnology, like antibodies, enzymes, aptamers, and MIP-like macromolecules, improves stability, selectivity, sensitivity, and speed of detection. Furthermore, bacterial, fungal, algal, and mammalian cells are all cell-based biosensors used in pesticide and herbicide detection, helping to establish fast, reliable, real-time, and cost-effective tools for decontamination procedures and preventive casualty damage.

Carcinogens, odorants, and marine contaminants are other toxins that are significant in food production. Carcinogens are a complex group of trace amount of toxins, like pesticides, heavy metals, mycotoxins, and acrylamide, in which the difficulty of identifying trace-amounts is a challenge; and imprinted aptamers, nanotechnology, and biosensing are optimistic for promising future use. Sensitive and soluble molecules effective in odour detection for olfactory animal systems are odorant binding proteins. A nanosensor combining localized SPR and small odorant binding proteins from honeybees has been established in which the detection range is 10 nM – 1 mM using a quantitative array of nanocups. To monitor and preserve a stable environment for marine food systems, marine contaminant detection is used. Finally, through their sensitive detection capabilities, miniaturized devices, wireless communication, and small-scale networks, biosensors can be applied to marine food safety to be established as advanced analytical and monitoring tools.

Another development kit for food safety biosensors focuses on the detection of genetically modified organisms (GMOs) in food products. Since the 1990s, GMOs in all fields of agricultural products have been considered a biotechnology revolution. To present, more than 45 percent of the world’s soybeans, 40 percent of corn, and 50 percent of cotton are GM products; and GM is also used in livestock. Recent research, however, indicates that GMO products can affect human and animal bodies through gastrointestinal problems, antibiotic resistance, allergenicity, diversity of farm products degradation, and undesired gene flow to other species. Biosensors are designed to measure GMOs in foods and feeds using isothermal DNA amplification and fast detection signal detection to identify GM genes. Detecting unidentified DNA genes that can be resolved by high-throughput technology like the combination of biosensing and arrays, and the development of databases of GMO genes are the key challenges in GMO detection.

Biosensors & Biochips for environmental monitoring

Due to the strong connection between environmental pollution and human health/ socioeconomic progress, environmental monitoring has become one of the priorities on a European and global scale. Biosensors have been commonly used as cost-effective, rapid, in situ, and real-time analytical techniques in this field. The recent development of biosensors with new transduction materials obtained from nanotechnology and for multiplexed pollutant detection, involving multidisciplinary experts, explains the need for compact, fast, and smart biosensing devices. Several recent developments exist in the monitoring of air, water, and soil contaminants by biosensors under real conditions, like pesticides, highly toxic components and small organic molecules, including toxins and endocrine disrupting chemicals.

Biosensors used in environmental monitoring can be categorized as optical (including optical fibre and surface plasmon resonance biosensors), electrochemical (including amperometric and impedance biosensors) and piezoelectric (including quartz crystal microbalance biosensors) based on their transduction or as immunosensors, aptasensors, genosensors and enzymatic biosensors based on their recognition elements, respectively when are used antibodies, aptamers, nucleic acids, and enzymes. The majority of biosensors in environmental monitoring are recognized as immunosensors and enzymatic biosensors, but the development of aptasensors has recently increased due to the beneficial characteristics of aptamers, like ease of modification, thermal stability, in vitro synthesis and the ability to design their structure, to differentiate targets with different functional groups and to rehybridize.

Study on the design of biosensors for the monitoring of organic pollutants, potentially toxic elements and pathogens in the environment has led to the sustainable development of civilization due to the environmental pollution issues confronting human health. Various chromatographic techniques (such as gas chromatography and high-performance liquid chromatography combined with capillary electrophoresis or mass spectrometry) are conventional analytical methods used for environmental monitoring of pollutants, but they require costly reagents, time-consuming sample pre-treatment and costly equipment. Therefore, for monitoring pollutants responsible for adverse effects on habitats and human health, more sensitive, cost-effective, fast, easy to function, and compact biosensing devices are desperately needed to overcome the magnification of environmental issues. In the case of accidental release of pesticides or acute poisoning, for example, common methods are not appropriate for in situ measurements where fast, miniaturized, and portable equipment like environmental monitoring biosensors is required. In this regard, the role of nanotechnology in the creation of rapid and intelligent biosensing devices is crucial for the success of environmental pollutant detection; most recent biosensors include nanomaterials and novel nanocomposites in their systems, which are beneficial for improving analytical performance, such as sensitivity and detection limits.

For the detection and monitoring of different environmental pollutants, biosensors, including immunosensors, aptasensors, genosensors and enzymatic biosensors have been documented using antibodies, aptamers, nucleic acids, and enzymes as recognition elements.

Pesticides

Pesticides are among the most significant environmental pollutants because of their large presence in the environment. Organophosphorus insecticides, for example, are commonly used in agriculture and represent a group of pesticides which, due to their high toxicity, are of immense environmental concern. Easy, responsive, and miniaturized in situ methodologies like biosensors have therefore been established as analytical strategies for their detection and monitoring, without the need for comprehensive sample pre-treatment.

Disposable amperometric enzymatic (acetylcholinesterase) biosensors were proposed for the detection of organophosphorus insecticides using paraoxon as a model analyte applying a cysteamine self-assembled monolayer on gold screen-printed electrodes. The disposable biosensors showed a linear spectrum of up to 40 ppb with a 2 ppb detection limit and a 113 μA mM cm-2 sensitivity. Using the self-assembled monolayer, good analytical output could be due to the highly oriented enzyme immobilization. Recoveries of 97 ± 5 percent (n = 3) were reported after being tested in river water samples spiked with 10 ppb of paraoxon, indicating the effectiveness of such enzymatic biosensors. Furthermore, the use of disposable screen-printed electrodes dispenses with time-consuming methods like the reactivation of immobilized enzymes utilizing, for example, obidoxime solution and pralidoxime iodide (PAM) or the use of the renewable enzyme membrane needed for the second application of biosensors.

Nanoparticles based on iridium oxide have been used in the disposable enzymatic biosensor with tyrosinase based on low-cost screen-printed carbon electrodes for the detection of chlorpyrifos in river water samples. Linear biosensor response (0.01–0.1 μM) and low detection limit (3 nM) were reported, which could be due to the high conductivity of nanoparticles of iridium oxide and tyrosinase efficiency. Recovery tests were carried out in river water samples with the addition of 0.1 μM of chlorpyrifos and recoveries of 90 ± 9.6 percent were obtained with a residual standard deviation (RSD) smaller than 10 percent (n = 3) to demonstrate the applicability of the biosensor.

Acetamiprid was detected by colorimetric aptasensors and water samples by impedimetric aptasensors in real environmental samples, like fresh surface soil samples. A linear range of 75 nM to 7.5 μM and a detection limit of 5 nM were observed with the colorimetric aptasensor, while a wider linear range (50 fM to 10 μM) and a lower detection limit (17 fM) were observed with the impedimetric aptasensor. Gold nanoparticles, multi-walled carbon nanotubes (MWCNT) and reduced graphene oxide nanoribbons were used in that biosensor as a composite to sustain the electrode surface acetamiprid aptamer, which could be responsible for higher electron transfer and improved analytical performance of the biosensor. A related detection limit (33 fM) was observed by an aptasensor based on silver nanoparticles anchored on nitrogen-doped nanocomposite graphene oxide constructed for acetamiprid detection in wastewater samples.

Pathogens

The existence of pathogens in environmental matrices, and especially in water compartments, could pose a serious risk to human health, and some biosensors have recently been suggested for monitoring the environment. For example, for the detection of metabolically active Legionella pneumophila in complex environmental water samples, rapid and precise optical biosensors based on surface plasmon resonance have been proposed. In one study, the detection principle was based on the identification of bacterial RNA by the immobilized RNA detector probe on the gold surface of the biochip. For signal amplification, streptavidin-conjugated quantum dots were used, and the detection period was approximately three hours, indicating the viability of the biosensing device for successful bacteria detection in the range of 104-108 CFU mL-1.

Potentially toxic elements

The contamination by heavy metals and corresponding ions of the natural waters can pose significant risks to human health, and compact, low-cost, and rapid heavy metal analyses are a global priority concern. As a model target for testing an optical DNA biosensor for the detection of heavy metal ions that are extremely toxic and common pollutants in the environment, mercury ions (Hg2+) were used. The biosensor was compact, low-cost, and rapid with in situ screening of Hg2+ in natural waters in less than 10 min. The detection principle is focused on the capacity of certain metal ions to bind selectively to certain bases to form stable metal-mediated DNA duplexes; in the case of Hg2+, thymine bases can be selectively coordinated to form stable thymine-Hg2+-thymine complexes. In the detection range between 0 and 1000 nM, a detection limit of 1.2 nM was achieved, which is lower than the maximum value requested by the United States Environmental Protection Agency (10 nM)

For the detection of Pb2+ in water samples (pond and lake water samples) using DNAzymes/carboxylated magnetic beads and DNA aptamers, two fluorescence based optical biosensors have recently been suggested. The detection limits of 5 nM and 61 nM, respectively, were observed by biosensors based on DNAzymes and DNA aptamers, with a respective linear detection range of 0 to 50 nM and 100 to 1000 nM. The use of label-free unique dye (SYBER Green I), which was intercalated with double stranded DNA, showing strong fluorescence intensities, as seen in Figure 5. Moreover, the absence of biosensor fluorescence intensity is observed only with the dye (curve a). With the DNAzyme + Pb2+ (curve b) the fluorescence intensity increases with the addition of the dye + DNAzyme + Pb2+, illustrating the sensitivity of the biosensor towards Pb2+.

Figure 5. Fluorescence emission spectra for detection of Pb2+

Toxins

Harmful toxins like brevetoxins and microcystins are created by the eutrophication of aquatic systems by the algal blooms of cyanobacteria, and thus accurate and cost-effective systems are needed for the early detection of such toxins. For the sensitive detection of brevetoxin-2, a marine neurotoxin, an electrochemical aptasensor has been used composed by gold electrodes functionalized with cysteamine self-assembled monolayers. A detection limit of 106 pg mL-1 was achieved and strong selectivity was observed for brevetoxin-2 against other toxins of various groups, like okadaic acid and microcystin. The feasibility of the aptasensor for detecting brevetoxin-2 in real samples was achieved by analysing shellfish and strong recoveries (102-110 percent) were reported, indicating no interaction with the aptasensor response from the shellfish matrix.

Endocrine disrupting chemicals

In water samples, bisphenol A was detected as an endocrine disrupting chemical by aptasensors based on the fluorescence principle with functionalized aptamers (fluorescein amidite) and gold nanoparticles and based on evanescent-wave optical fibre. The evanescent-wave optical fibre aptasensor was compact and found to be rapid, cost-effective, sensitive and selective for the detection of bisphenol A in water samples, with the benefit of no requirement of any pre-concentration or treatment steps.  Furthermore, the aptasensor can be reused for 90 s by regeneration with a 0.5% sodium dodecyl sulphate (SDS) solution and further washing with a phosphate buffered saline (PBS) solution (pH 7.2) for over a hundred assay cycles without any noticeable loss of efficiency. Similar detection limits (0.1 and 0.45 ng mL-1) were observed in both optical biosensors where the DNA molecule probe, which is the complementary sequence of a small fraction of the bisphenol A aptamer, was adsorbed by electrostatic interaction in the surface of gold nanoparticles and covalently immobilized on the surface of the fibre. Lately, for the detection of bisphenol A in river water samples using molybdenum carbide nanotubes, another fluorescence-based aptasensor was proposed. With such a label-free, inexpensive, and easy to use aptasensor, a low detection limit of 0.23 ng mL−1 has been obtained. The specificity of the aptasensor was evaluated by analysing other molecules with structures similar to that of bisphenol A (e.g., 4,4J-biphenol, bisphenol AF, and 4,4J-sulfonyldiphenol) and only background signals showing high specificity for bisphenol A were identified for these molecules.

A disposable and label-free electrochemical immunosensor based on a field effect transistor with SWCNT has recently been employed in seawater samples for assessing another endocrine disrupting chemical – 4-nonylphenol. The immunosensor has a high reproducibility (0.56 ± 0.08%), an average recovery of 97.8% to 104.6% and a low detection limit (5 μg L-1), which is lower than the recommended maximum concentration of 7 μg L-1 specified by the corresponding regulations. In seawater samples such as 4-nonylphenol, the biosensor could be used to detect hazardous priority substances, even at low concentrations and with an easy and low-cost methodology.

Other environmental compounds

New, fast, and accurate analytical methodologies have been needed for the early detection and monitoring of various other hazardous compounds liberated during algal blooms. Due to the excellent sensitivity and specificity of nucleic acid probes to their complementary binding partners, biosensors have been developed to detect algal RNA. For the enhanced selective and sensitive detection of RNA from 13 harmful algal organisms, an electrochemical genosensor based on screen-printed gold electrode was recently reported; the genosensor could distinguish RNA targets from environmental samples (spiked seawater samples) containing 105 cells, considered to be the limit of detection.

Test: LO3 Advanced Level

Welcome to your LO3-Advanced level

References

  • Adami A; Mortari A; Morganti E; Lorenzelli L. 2018. Microfluidic Sample Preparation Methods for the Analysis of Milk Contaminants. Available online: https://www.hindawi.com/journals/js/2016/2385267/
  • Al-Mawali A. 2015. Non-communicable diseases: shining a light on cardiovascular dis- ease, Oman’s biggest killer. Oman Med. J., 30 (4): 227.
  • Arduini F, Guidone S, Amine A, Palleschi G, Moscone D. 2013. Acetylcholinesterase biosensor based on self-assembled monolayer-modified gold-screen printed electrodes for organophosphorus insecticide detection. Sens. Actuators B Chem., 179: 201–208.
  • Arduini F, Cinti S, Scognamiglio V, Moscone D. 2016. Nanomaterials in electrochemical biosensors for pesticide detection: advances and challenges in food analysis. Microchim. Acta, 183: 2063–2083.
  • Arugula MA, Simonian AL. 2016. Biosensors for Detection of Genetically Modified Organisms in Food and Feed. In Genetically Modified Organisms in Food, Elsevier: Amsterdam, The Netherlands, pp. 97–110, ISBN 978-0-12-802259-7.
  • Ayari-Jeridi H. et al. 2015. Mutation spectrum of RB1 gene in unilateral retinoblastoma cases from Tunisia and correlations with clinical features. PLoS One, 10 (1): e0116615.
  • Bahadır EB, Sezgintürk MK. 2017. Biosensor technologies for analyses of food contaminants. In Nanobiosensors, Elsevier: Amsterdam, The Netherlands, pp. 289–337, ISBN 978-0-12-804301-1.
  • Baldwin CJ. 2015. Introduction to the Principles. In The 10 Principles of Food Industry Sustainability, John Wiley & Sons, Ltd.: Hoboken, NJ, USA, pp. 1–14, ISBN 978-1-118-44769-7.
  • Beck MB, Walker VR. 2013. On water security, sustainability, and the water-food-energy-climate nexus. Front. Environ. Sci. Eng., 7: 626–639.
    Belkhamssa N, da Costa JP, Justino CIL, Santos PSM, Cardoso S, Duarte AC, Rocha-Santos T, Ksibi M. 2016. Development of an electrochemical biosensor for alkylphenol detection. Talanta, 158: 30–34.
  • Bhalla N. et al. 2016. Introduction to biosensors. Essays Biochem., 60 (1): 1–8.
  • Bohunicky B, Mousa SA. 2011. Biosensors: the new wave in cancer diagnosis. Nanotechnol. Sci. Appl., 4: 1.
  • Bourne MC. 2014. Food Security: Postharvest Losses. In Encyclopedia of Agriculture and Food Systems, Elsevier: Amsterdam, The Netherlands, pp. 338–351, ISBN 978-0-08-093139-5.
  • Bruen D et al. 2017. Glucose sensing for diabetes monitoring: recent developments. Sensors, 1866.
  • Burris KP, Stewart CN. 2012. Fluorescent nanoparticles: Sensing pathogens and toxins in foods and crops. Trends Food Sci. Technol., 28: 143–152.
    Byrne B et al. 2009. Antibody-based sensors: principles, problems and potential for detection of pathogens and associated toxins. Sensors, 9 (6): 4407–4445.
  • Cash KJ, Clark HA. 2010. Nanosensors and nanomaterials for monitoring glucose in diabetes. Trends Mol. Med., 16 (12): 584–593.
  • Chao R, Mishra S, Si T, Zhao H. 2017. Engineering biological systems using automated biofoundries. Metab. Eng., 42: 98–108.
  • Chen Y, Li H, Gao T, Zhang T, Xu L, Wang B, Wang J, Pei R. 2018. Selection of DNA aptamers for the development of light-up biosensor to detect Pb(II). Sens. Actuators B Chem., 254: 214–221.
  • Eissa S, Siaj M, Zourob M. 2015. Aptamer-based competitive electrochemical biosensor for brevetoxin-2. Biosens. Bioelectron., 69: 148–154.
  • Elmore S. 2007. Apoptosis: a review of programmed cell death. Toxicol. Pathol., 35 (4): 495–516.
  • Enrico DL, Manera MG, Montagna G, Cimaglia F, Chesa M, Poltronieri P, Santino A, Rella R. 2013. PR based immunosensor for detection of Legionella pneumophila in water samples. Opt. Commun., 294: 420–426.
  • EPA. National Recommended Water Quality Criteria—Aquatic Life Criteria Table. Available online: http://www.epa.gov/wqc/national-recommended-water-quality-criteria-aquatic-life-criteria-table
  • Fei A, Liu Q, Huan J, Qian J, Dong X, Qiu B, Mao H, Wang K. 2015. Label-free impedimetric aptasensor for detection of femtomole level acetamiprid using gold nanoparticles decorated multiwalled carbon nanotube-reduced graphene oxide nanoribbon composites. Biosens. Bioelectron., 70: 122–129.
  • Foudeh AM, Trigui H, Mendis N, Faucher SP, Veres T, Tabrizian M. 2015. Rapid and specific SPRi detection of L. pneumophila in complex environmental water samples. Anal. Bioanal. Chem., 407: 5541–5545.
  • Garnet TF. 2013. Food sustainability: Problems, perspectives and solutions. Proc. Nutr. Soc., 72: 29–39.
  • Gheorghe I, Czobor I, Lazar V, Chifiriuc MC 2017. Present and perspectives in pesticides biosensors development and contribution of nanotechnology. In New Pesticides and Soil Sensors, Elsevier: Amsterdam, The Netherlands, pp. 337–372, ISBN 978-0-12-804299-1.
  • Ghorashi M. 2018. Technology’s Role in Eradicating Foodborne Illness. Available online: https://www.foodsafetymagazine.com/signature-series/technologye28099s-role-in-eradicating-foodborne-illness/
  • Giacinti C, Giordano A. 2006. RB and cell cycle progression. Oncogene, 25 (38): 5220–5227.
  • Guo L, Li Z, Chen H, et al. 2017. Colorimetric biosensor for the assay of paraoxon in environmental water samples based on the iodine-starch color reaction. Anal. Chim. Acta, 967: 59–63.
  • Hameed I, et al. 2015. Type 2 diabetes mellitus: from a metabolic disorder to an inflammatory condition. World J. Diabetes, 6 (4): 598.
    Hassani S, Momtaz S, Vakhshiteh F, et al. 2017. Biosensors and their applications in detection of organophosphorus pesticides in the environment. Arch. Toxicol., 91: 109–130.
  • He MQ, Wang K, Wang J, Yu YL, He RH. 2017. A sensitive aptasensor based on molybdenum carbide nanotubes and label-free aptamer for detection of bisphenol A. Anal. Bioanal. Chem., 409: 1797–1803.
  • Holford TR et al. 2012. Recent trends in antibody based sensors. Biosens. Bioelectron., 34 (1): 12–24.
  • Hughes RA, Ellington AD. 2017. Synthetic DNA synthesis and assembly: Putting the synthetic in synthetic biology. Cold Spring Harb. Perspect. Biol., 9.
  • Husu I, Rodio G, Touloupakis E, et al. 2013. Insights into photo-electrochemical sensing of herbicides driven by Chlamydomonas reinhardtii cells. Sens. Actuators B Chem., 185: 321–330.
  • Jain KK. 2004. “Applications of biochips: from diagnostics to personalized medicine.” Curr Opin Drug Discov Devel, 7(3): 285-289.
  • Jiang D, Du X, Liu Q, Zhou L, Dai L, Qian J, Wang K. 2015. Silver nanoparticles anchored on nitrogen-doped graphene as a novel electrochemical biosensing platform with enhanced sensitivity for aptamer-based pesticide assay. Analyst, 140: 6404–6411.
  • Justino CIL, Freitas AC, Duarte AC, Santos TAPR. 2015. Sensors and biosensors for monitoring marine contaminants. Trends Environ. Anal. Chem., 6–7: 21–30.
  • Justino CIL, Freitas AC, Pereira R, Duarte AC, Rocha-Santos TAP. 2015. Recent developments in recognition elements for chemical sensors and biosensors. Trends Anal. Chem., 68: 2–17.
  • Kazemi-Darsanaki R et al. 2012. Biosensors: functions and applications. J. Biol. Today’s World, 2 (1): 20–23.
  • Khot LR, Sankaran S, Maja JM, Ehsani R, Schuster EW. 2012. Applications of nanomaterials in agricultural production and crop protection: A review. Crop Prot., 35: 64–70.
  • Kost GJ, Tran NK., 2005. Point-of-care testing and cardiac biomarkers: the standard of care and vision for chest pain centers. Cardiol. Clin., 23 (4): 467–490.
  • Lang Q, Han L, Hou C, Wang F, Liu A. 2016. A sensitive acetylcholinesterase biosensor based on gold nanorods modified electrode for detection of organophosphate pesticide. Talanta, 156: 34–41.
  • Lee EY, Muller WJ. 2010. Oncogenes and tumor suppressor genes. Cold Spring Harb. Perspect. Biol., 2 (10): a003236.
  • Li Z, Yu Y, Li Z, Wu T. 2015. A review of biosensing techniques for detection of trace carcinogen contamination in food products. Anal. Bioanal. Chem., 407: 2711–2726.
  • Liao W, Lu X. 2016. Determination of chemical hazards in foods using surface-enhanced Raman spectroscopy coupled with advanced separation techniques. Trends Food Sci. Technol., 54: 103–113.
  • Long F, Zhu A, Shi H, Wang H, Liu J. 2013. Rapid on-site/in-situ detection of heavy metal ions in environmental water using a structure-switching DNA optical biosensor. Sci. Rep., 3: 2308.
  • Loo C, et al. 2005. Immunotargetednanoshells for integrated cancer imaging and therapy. Nano Lett., 5 (4): 709–711.
  • Maduraiveeran G, Jin W. 2017. Nanomaterilas based electrochemical sensor and biosensor platforms for environmental applications. Trends Environ. Anal. Chem., 13: 10–23.
  • Marcellin E, Nielsen LK 2018. Advances in analytical tools for high throughput strain engineering. Curr. Opin. Biotechnol., 54: 33–40.
  • Martín-Timón I et al. 2014. Type 2 diabetes and cardiovascular disease: have all risk factors the same strength? World J. Diabetes, 5 (4): 444.
  • Mayorga-Martinez C, Pino F, Kurbanoglua S, et al. 2014. Iridium oxide nanoparticles induced dual catalytic/inhibition based detection of phenol and pesticide compounds. J. Mater. Chem. B, 2: 2233–2239.
  • McPartlin DA, Loftus JH, Crawley AS, et al. 2017. Biosensors for the monitoring of harmful algal blooms. Curr. Opin. Biotechnol., 45: 164–169.
  • Mehrotra P. 2016. Biosensors and their applications – a review. J. Oral. Biol. Craniofac Res., 6 (2): 153–159.
  • Meriç S, Çakır Ö, Turgut-Kara N, Arı S. 2014. Detection of genetically modified maize and soybean in feed samples. Genet. Mol. Res., 13: 1160–1168.
  • Moran KLM, Fitzgerald J, McPartlin DA, Loftus JH, O’Kennedy R. 2016. Biosensor-Based Technologies for the Detection of Pathogens and Toxins. In Comprehensive Analytical Chemistry, Elsevier: Amsterdam, The Netherlands, Volume 74, pp. 93–120, ISBN 978-0-444-63579-2.
  • Mungroo NA, Neethirajan S. 2014. Biosensors for the Detection of Antibiotics in Poultry Industry—A Review. Biosensors, 4: 472–493.
  • Ngoepe M et al. 2013. Integration of biosensors and drug delivery technologies for early detection and chronic management of illness. Sensors, 13 (6): 7680–7713.
  • Omidfar K. et al. 2013. New analytical applications of gold nanoparticles as label in antibody based sensors. Biosens. Bioelectron., 43: 336–347.
    Orozco J, Villa E, Manes C, Medlin LK, Guillebault D. 2016. Electrochemical RNA genosensors for toxic algal species: Enhancing selectivity and sensitivity. Talanta, 161: 560–566.
  • Patra S, Roy E, Madhuri R, Sharma PK. 2017. A technique comes to life for security of life: The food contaminant sensors. In Nanobiosensors, Elsevier: Amsterdam, The Netherlands, pp. 713–772, ISBN 978-0-12-804301-1.
  • Pola-López LA, Camas-Anzueto JL, Martínez-Antonio A, et al. 2018. Novel arsenic biosensor “POLA” obtained by a genetically modified E. coli bioreporter cell. Sens. Actuators B Chem., 254: 1061–1068.
  • Ragavan KV, Selvakumar LS, Thakur MS. 2013. Functionalized aptamers as nano-bioprobes for ultrasensitive detection of bisphenol-A. Chem. Commun., 49: 5960–5962.
  • Rapini R, Marrazza G. 2016. Biosensor Potential in Pesticide Monitoring. In Comprehensive Analytical Chemistry, Elsevier: Amsterdam, The Netherlands, Volume 74, pp. 3–31, ISBN 978-0-444-63579-2.
  • Ravikumar A, Panneerselvam P, Radhakrishnan K, et al. 2017. DNAzyme based amplified biosensor on ultrasensitive fluorescence detection of Pb(II) ions from aqueous system. J. Fluoresc., 27: 2101–2109.
  • Rocchitta G, et al. 2016. Enzyme biosensors for biomedical applications: strategies for safeguarding analytical performances in biological fluids. Sensors, 16 (6).
  • Rotariu L, Lagarde F, Jaffrezic-Renault N, Bala C. 2016. Electrochemical biosensors for fast detection of food contaminants—Trends and perspective. TrAC Trends Anal. Chem., 79: 80–87.
  • Saucedo NM, Mulchandan A. 2016. Sensing of Biological Contaminants. In Comprehensive Analytical Chemistry, Elsevier: Amsterdam, The Netherlands, Volume 74, pp. 73–91, ISBN 978-0-444-63579-2.
  • Shi H, Zhao G, Liu M, Fan L, Cao T. 2013. Aptamer-based colorimetric sensing of acetamiprid in soil samples: Sensitivity, selectivity and mechanism. J. Hazard. Mater., 260: 754–761.
  • Singh M, del Valle M. 2015. Arsenic Biosensors. In Handbook of Arsenic Toxicology, Elsevier: Amsterdam, The Netherlands, pp. 575–588, ISBN 978-0-12-418688-0.
  • Sinha K, Ghosh J, Sil PC. 2017. New pesticides: A cutting-edge view of contributions from nanotechnology for the development of sustainable agricultural pest control. In New Pesticides and Soil Sensors, Elsevier: Amsterdam, The Netherlands, pp. 47–79, ISBN 978-0-12-804299-1.
  • Sodano V, Gorgitano MT, Quaglietta M, Verneau F. 2016. Regulating food nanotechnologies in the European Union: Open issues and political challenges. Trends Food Sci. Technol., 54: 216–226.
  • Specht K, Siebert R, Hartmann I, et al. 2014. Urban agriculture of the future: An overview of sustainability aspects of food production in and on buildings. Agric. Hum. Values, 31: 33–51.
  • Stadler RH. 2016. Foreword for Food Processing—Derived Contaminants in Food Analysis. In Reference Module in Food Science, Elsevier: Amsterdam, The Netherlands, ISBN 978-0-08-100596-5.
  • Tabish SA. 2007. Is diabetes becoming the biggest epidemic of the twenty-first century? Int J. Health Sci. 1 (2), V–VIII.
  • Templier V, Roux A, Roupioz Y, Livache T. 2016. Ligands for label-free detection of whole bacteria on biosensors: A review. TrAC Trends Anal. Chem., 79: 71–79.
  • Thomas S, et al. 2015. The expression of retinoblastoma tumor suppressor protein in oral cancers and precancers: a clinicopathological study. Dent. Res. J., 12 (4): 307.
  • Tian L, Hires SA, Mao T, et al. 2009. Imaging neural activity in worms, flies and mice with improved GAaMP calcium indicators. Nat. Methods, 6: 875–881.
  • Turner AP. 2013. Biosensors: Sense and sensibility. Chem. Soc. Rev., 42: 3184–3196.
  • USEPA. Mercury Update: Impact of Fish Advisories, EPA Fact Sheet EPA-823-F-01-011, EPA, Office of Water: Washington, DC, USA, 2001.
  • Valastyan S, Weinberg RA. 2011. Tumor metastasis: molecular insights and evolving paradigms. Cell, 147 (2): 275–292.
  • Verma N, Kaur G. 2016. Trends on Biosensing Systems for Heavy Metal Detection. In Comprehensive Analytical Chemistry, Elsevier: Amsterdam, The Netherlands, Volume 74, pp. 33–71, ISBN 978-0-444-63579-2.
  • Vu T, Claret FX. 2012. Trastuzumab: updated mechanisms of action and resistance in breast cancer. Front. Oncol., 2: 62.
  • Way JC, Collins JJ, Keasling JD, Silver PA. 2014. Integrating biological redesign: Where synthetic biology came from and where it needs to go. Cell, 157: 151–161.
  • Weng X, Neethirajan S. 2017. Ensuring food safety: Quality monitoring using microfluidics. Trends Food Sci. Technol., 65: 10–22.
  • Xiao Y, Lubin AA, Heeger AJ, Plaxco KW. 2005. Label-free electronic detection of thrombin in blood serum by using an aptamer-based sensor. Angew. Chem. Int. Ed. Engl., 44: 5456–5459.
  • Yildirim N, Long F, He M, Shi HC, Gu AZ. 2014. A portable optic fiber aptasensor for sensitive, specific and rapid detection of bisphenol-A in water samples. Environ. Sci. Process Impacts, 16: 1379–1386.
  • Yoshida K, Miki Y. 2004. Role of BRCA1 and BRCA2 as regulators of DNA repair, transcription, and cell cycle in response to DNA damage. Cancer Sci., 95 (11): 866–871.
  • Zhang D, Lu Y, Zhang Q, et al. 2015. Nanoplasmonic monitoring of odorants binding to olfactory proteins from honeybee as biosensor for chemical detection. Sens. Actuators B Chem., 221: 341–349.
  • Zhang F, Zhang Q, Zhang D, Lu Y, Liu Q, Wang P. 2014. Biosensor analysis of natural and artificial sweeteners in intact taste epithelium. Biosens. Bioelectron., 54: 385–392.
  • Zhang W, Asiri AM, Liu D, Du D, Lin Y. 2015. Nanomaterial-based biosensors for environmental and biological monitoring of organophosphorus pesticides and nerve agents. Trends Anal. Chem., 54: 1–10.
  • Adami A; Mortari A; Morganti E; Lorenzelli L. 2018. Microfluidic Sample Preparation Methods for the Analysis of Milk Contaminants. Available online: https://www.hindawi.com/journals/js/2016/2385267/
  • Al-Mawali A. 2015. Non-communicable diseases: shining a light on cardiovascular dis- ease, Oman’s biggest killer. Oman Med. J., 30 (4): 227.
  • Arduini F, Guidone S, Amine A, Palleschi G, Moscone D. 2013. Acetylcholinesterase biosensor based on self-assembled monolayer-modified gold-screen printed electrodes for organophosphorus insecticide detection. Sens. Actuators B Chem., 179: 201–208.
  • Arduini F, Cinti S, Scognamiglio V, Moscone D. 2016. Nanomaterials in electrochemical biosensors for pesticide detection: advances and challenges in food analysis. Microchim. Acta, 183: 2063–2083.
  • Arugula MA, Simonian AL. 2016. Biosensors for Detection of Genetically Modified Organisms in Food and Feed. In Genetically Modified Organisms in Food, Elsevier: Amsterdam, The Netherlands, pp. 97–110, ISBN 978-0-12-802259-7.
  • Ayari-Jeridi H. et al. 2015. Mutation spectrum of RB1 gene in unilateral retinoblastoma cases from Tunisia and correlations with clinical features. PLoS One, 10 (1): e0116615.
  • Bahadır EB, Sezgintürk MK. 2017. Biosensor technologies for analyses of food contaminants. In Nanobiosensors, Elsevier: Amsterdam, The Netherlands, pp. 289–337, ISBN 978-0-12-804301-1.
  • Baldwin CJ. 2015. Introduction to the Principles. In The 10 Principles of Food Industry Sustainability, John Wiley & Sons, Ltd.: Hoboken, NJ, USA, pp. 1–14, ISBN 978-1-118-44769-7.
  • Beck MB, Walker VR. 2013. On water security, sustainability, and the water-food-energy-climate nexus. Front. Environ. Sci. Eng., 7: 626–639.
    Belkhamssa N, da Costa JP, Justino CIL, Santos PSM, Cardoso S, Duarte AC, Rocha-Santos T, Ksibi M. 2016. Development of an electrochemical biosensor for alkylphenol detection. Talanta, 158: 30–34.
  • Bhalla N. et al. 2016. Introduction to biosensors. Essays Biochem., 60 (1): 1–8.
  • Bohunicky B, Mousa SA. 2011. Biosensors: the new wave in cancer diagnosis. Nanotechnol. Sci. Appl., 4: 1.
  • Bourne MC. 2014. Food Security: Postharvest Losses. In Encyclopedia of Agriculture and Food Systems, Elsevier: Amsterdam, The Netherlands, pp. 338–351, ISBN 978-0-08-093139-5.
  • Bruen D et al. 2017. Glucose sensing for diabetes monitoring: recent developments. Sensors, 1866.
  • Burris KP, Stewart CN. 2012. Fluorescent nanoparticles: Sensing pathogens and toxins in foods and crops. Trends Food Sci. Technol., 28: 143–152.
    Byrne B et al. 2009. Antibody-based sensors: principles, problems and potential for detection of pathogens and associated toxins. Sensors, 9 (6): 4407–4445.
  • Cash KJ, Clark HA. 2010. Nanosensors and nanomaterials for monitoring glucose in diabetes. Trends Mol. Med., 16 (12): 584–593.
  • Chao R, Mishra S, Si T, Zhao H. 2017. Engineering biological systems using automated biofoundries. Metab. Eng., 42: 98–108.
  • Chen Y, Li H, Gao T, Zhang T, Xu L, Wang B, Wang J, Pei R. 2018. Selection of DNA aptamers for the development of light-up biosensor to detect Pb(II). Sens. Actuators B Chem., 254: 214–221.
  • Eissa S, Siaj M, Zourob M. 2015. Aptamer-based competitive electrochemical biosensor for brevetoxin-2. Biosens. Bioelectron., 69: 148–154.
  • Elmore S. 2007. Apoptosis: a review of programmed cell death. Toxicol. Pathol., 35 (4): 495–516.
  • Enrico DL, Manera MG, Montagna G, Cimaglia F, Chesa M, Poltronieri P, Santino A, Rella R. 2013. PR based immunosensor for detection of Legionella pneumophila in water samples. Opt. Commun., 294: 420–426.
  • EPA. National Recommended Water Quality Criteria—Aquatic Life Criteria Table. Available online: http://www.epa.gov/wqc/national-recommended-water-quality-criteria-aquatic-life-criteria-table
  • Fei A, Liu Q, Huan J, Qian J, Dong X, Qiu B, Mao H, Wang K. 2015. Label-free impedimetric aptasensor for detection of femtomole level acetamiprid using gold nanoparticles decorated multiwalled carbon nanotube-reduced graphene oxide nanoribbon composites. Biosens. Bioelectron., 70: 122–129.
  • Foudeh AM, Trigui H, Mendis N, Faucher SP, Veres T, Tabrizian M. 2015. Rapid and specific SPRi detection of L. pneumophila in complex environmental water samples. Anal. Bioanal. Chem., 407: 5541–5545.
  • Garnet TF. 2013. Food sustainability: Problems, perspectives and solutions. Proc. Nutr. Soc., 72: 29–39.
  • Gheorghe I, Czobor I, Lazar V, Chifiriuc MC 2017. Present and perspectives in pesticides biosensors development and contribution of nanotechnology. In New Pesticides and Soil Sensors, Elsevier: Amsterdam, The Netherlands, pp. 337–372, ISBN 978-0-12-804299-1.
  • Ghorashi M. 2018. Technology’s Role in Eradicating Foodborne Illness. Available online: https://www.foodsafetymagazine.com/signature-series/technologye28099s-role-in-eradicating-foodborne-illness/
  • Giacinti C, Giordano A. 2006. RB and cell cycle progression. Oncogene, 25 (38): 5220–5227.
  • Guo L, Li Z, Chen H, et al. 2017. Colorimetric biosensor for the assay of paraoxon in environmental water samples based on the iodine-starch color reaction. Anal. Chim. Acta, 967: 59–63.
  • Hameed I, et al. 2015. Type 2 diabetes mellitus: from a metabolic disorder to an inflammatory condition. World J. Diabetes, 6 (4): 598.
    Hassani S, Momtaz S, Vakhshiteh F, et al. 2017. Biosensors and their applications in detection of organophosphorus pesticides in the environment. Arch. Toxicol., 91: 109–130.
  • He MQ, Wang K, Wang J, Yu YL, He RH. 2017. A sensitive aptasensor based on molybdenum carbide nanotubes and label-free aptamer for detection of bisphenol A. Anal. Bioanal. Chem., 409: 1797–1803.
  • Holford TR et al. 2012. Recent trends in antibody based sensors. Biosens. Bioelectron., 34 (1): 12–24.
  • Hughes RA, Ellington AD. 2017. Synthetic DNA synthesis and assembly: Putting the synthetic in synthetic biology. Cold Spring Harb. Perspect. Biol., 9.
  • Husu I, Rodio G, Touloupakis E, et al. 2013. Insights into photo-electrochemical sensing of herbicides driven by Chlamydomonas reinhardtii cells. Sens. Actuators B Chem., 185: 321–330.
  • Jain KK. 2004. “Applications of biochips: from diagnostics to personalized medicine.” Curr Opin Drug Discov Devel, 7(3): 285-289.
  • Jiang D, Du X, Liu Q, Zhou L, Dai L, Qian J, Wang K. 2015. Silver nanoparticles anchored on nitrogen-doped graphene as a novel electrochemical biosensing platform with enhanced sensitivity for aptamer-based pesticide assay. Analyst, 140: 6404–6411.
  • Justino CIL, Freitas AC, Duarte AC, Santos TAPR. 2015. Sensors and biosensors for monitoring marine contaminants. Trends Environ. Anal. Chem., 6–7: 21–30.
  • Justino CIL, Freitas AC, Pereira R, Duarte AC, Rocha-Santos TAP. 2015. Recent developments in recognition elements for chemical sensors and biosensors. Trends Anal. Chem., 68: 2–17.
  • Kazemi-Darsanaki R et al. 2012. Biosensors: functions and applications. J. Biol. Today’s World, 2 (1): 20–23.
  • Khot LR, Sankaran S, Maja JM, Ehsani R, Schuster EW. 2012. Applications of nanomaterials in agricultural production and crop protection: A review. Crop Prot., 35: 64–70.
  • Kost GJ, Tran NK., 2005. Point-of-care testing and cardiac biomarkers: the standard of care and vision for chest pain centers. Cardiol. Clin., 23 (4): 467–490.
  • Lang Q, Han L, Hou C, Wang F, Liu A. 2016. A sensitive acetylcholinesterase biosensor based on gold nanorods modified electrode for detection of organophosphate pesticide. Talanta, 156: 34–41.
  • Lee EY, Muller WJ. 2010. Oncogenes and tumor suppressor genes. Cold Spring Harb. Perspect. Biol., 2 (10): a003236.
  • Li Z, Yu Y, Li Z, Wu T. 2015. A review of biosensing techniques for detection of trace carcinogen contamination in food products. Anal. Bioanal. Chem., 407: 2711–2726.
  • Liao W, Lu X. 2016. Determination of chemical hazards in foods using surface-enhanced Raman spectroscopy coupled with advanced separation techniques. Trends Food Sci. Technol., 54: 103–113.
  • Long F, Zhu A, Shi H, Wang H, Liu J. 2013. Rapid on-site/in-situ detection of heavy metal ions in environmental water using a structure-switching DNA optical biosensor. Sci. Rep., 3: 2308.
  • Loo C, et al. 2005. Immunotargetednanoshells for integrated cancer imaging and therapy. Nano Lett., 5 (4): 709–711.
  • Maduraiveeran G, Jin W. 2017. Nanomaterilas based electrochemical sensor and biosensor platforms for environmental applications. Trends Environ. Anal. Chem., 13: 10–23.
  • Marcellin E, Nielsen LK 2018. Advances in analytical tools for high throughput strain engineering. Curr. Opin. Biotechnol., 54: 33–40.
  • Martín-Timón I et al. 2014. Type 2 diabetes and cardiovascular disease: have all risk factors the same strength? World J. Diabetes, 5 (4): 444.
  • Mayorga-Martinez C, Pino F, Kurbanoglua S, et al. 2014. Iridium oxide nanoparticles induced dual catalytic/inhibition based detection of phenol and pesticide compounds. J. Mater. Chem. B, 2: 2233–2239.
  • McPartlin DA, Loftus JH, Crawley AS, et al. 2017. Biosensors for the monitoring of harmful algal blooms. Curr. Opin. Biotechnol., 45: 164–169.
  • Mehrotra P. 2016. Biosensors and their applications – a review. J. Oral. Biol. Craniofac Res., 6 (2): 153–159.
  • Meriç S, Çakır Ö, Turgut-Kara N, Arı S. 2014. Detection of genetically modified maize and soybean in feed samples. Genet. Mol. Res., 13: 1160–1168.
  • Moran KLM, Fitzgerald J, McPartlin DA, Loftus JH, O’Kennedy R. 2016. Biosensor-Based Technologies for the Detection of Pathogens and Toxins. In Comprehensive Analytical Chemistry, Elsevier: Amsterdam, The Netherlands, Volume 74, pp. 93–120, ISBN 978-0-444-63579-2.
  • Mungroo NA, Neethirajan S. 2014. Biosensors for the Detection of Antibiotics in Poultry Industry—A Review. Biosensors, 4: 472–493.
  • Ngoepe M et al. 2013. Integration of biosensors and drug delivery technologies for early detection and chronic management of illness. Sensors, 13 (6): 7680–7713.
  • Omidfar K. et al. 2013. New analytical applications of gold nanoparticles as label in antibody based sensors. Biosens. Bioelectron., 43: 336–347.
    Orozco J, Villa E, Manes C, Medlin LK, Guillebault D. 2016. Electrochemical RNA genosensors for toxic algal species: Enhancing selectivity and sensitivity. Talanta, 161: 560–566.
  • Patra S, Roy E, Madhuri R, Sharma PK. 2017. A technique comes to life for security of life: The food contaminant sensors. In Nanobiosensors, Elsevier: Amsterdam, The Netherlands, pp. 713–772, ISBN 978-0-12-804301-1.
  • Pola-López LA, Camas-Anzueto JL, Martínez-Antonio A, et al. 2018. Novel arsenic biosensor “POLA” obtained by a genetically modified E. coli bioreporter cell. Sens. Actuators B Chem., 254: 1061–1068.
  • Ragavan KV, Selvakumar LS, Thakur MS. 2013. Functionalized aptamers as nano-bioprobes for ultrasensitive detection of bisphenol-A. Chem. Commun., 49: 5960–5962.
  • Rapini R, Marrazza G. 2016. Biosensor Potential in Pesticide Monitoring. In Comprehensive Analytical Chemistry, Elsevier: Amsterdam, The Netherlands, Volume 74, pp. 3–31, ISBN 978-0-444-63579-2.
  • Ravikumar A, Panneerselvam P, Radhakrishnan K, et al. 2017. DNAzyme based amplified biosensor on ultrasensitive fluorescence detection of Pb(II) ions from aqueous system. J. Fluoresc., 27: 2101–2109.
  • Rocchitta G, et al. 2016. Enzyme biosensors for biomedical applications: strategies for safeguarding analytical performances in biological fluids. Sensors, 16 (6).
  • Rotariu L, Lagarde F, Jaffrezic-Renault N, Bala C. 2016. Electrochemical biosensors for fast detection of food contaminants—Trends and perspective. TrAC Trends Anal. Chem., 79: 80–87.
  • Saucedo NM, Mulchandan A. 2016. Sensing of Biological Contaminants. In Comprehensive Analytical Chemistry, Elsevier: Amsterdam, The Netherlands, Volume 74, pp. 73–91, ISBN 978-0-444-63579-2.
  • Shi H, Zhao G, Liu M, Fan L, Cao T. 2013. Aptamer-based colorimetric sensing of acetamiprid in soil samples: Sensitivity, selectivity and mechanism. J. Hazard. Mater., 260: 754–761.
  • Singh M, del Valle M. 2015. Arsenic Biosensors. In Handbook of Arsenic Toxicology, Elsevier: Amsterdam, The Netherlands, pp. 575–588, ISBN 978-0-12-418688-0.
  • Sinha K, Ghosh J, Sil PC. 2017. New pesticides: A cutting-edge view of contributions from nanotechnology for the development of sustainable agricultural pest control. In New Pesticides and Soil Sensors, Elsevier: Amsterdam, The Netherlands, pp. 47–79, ISBN 978-0-12-804299-1.
  • Sodano V, Gorgitano MT, Quaglietta M, Verneau F. 2016. Regulating food nanotechnologies in the European Union: Open issues and political challenges. Trends Food Sci. Technol., 54: 216–226.
  • Specht K, Siebert R, Hartmann I, et al. 2014. Urban agriculture of the future: An overview of sustainability aspects of food production in and on buildings. Agric. Hum. Values, 31: 33–51.
  • Stadler RH. 2016. Foreword for Food Processing—Derived Contaminants in Food Analysis. In Reference Module in Food Science, Elsevier: Amsterdam, The Netherlands, ISBN 978-0-08-100596-5.
  • Tabish SA. 2007. Is diabetes becoming the biggest epidemic of the twenty-first century? Int J. Health Sci. 1 (2), V–VIII.
  • Templier V, Roux A, Roupioz Y, Livache T. 2016. Ligands for label-free detection of whole bacteria on biosensors: A review. TrAC Trends Anal. Chem., 79: 71–79.
  • Thomas S, et al. 2015. The expression of retinoblastoma tumor suppressor protein in oral cancers and precancers: a clinicopathological study. Dent. Res. J., 12 (4): 307.
  • Tian L, Hires SA, Mao T, et al. 2009. Imaging neural activity in worms, flies and mice with improved GAaMP calcium indicators. Nat. Methods, 6: 875–881.
  • Turner AP. 2013. Biosensors: Sense and sensibility. Chem. Soc. Rev., 42: 3184–3196.
  • USEPA. Mercury Update: Impact of Fish Advisories, EPA Fact Sheet EPA-823-F-01-011, EPA, Office of Water: Washington, DC, USA, 2001.
  • Valastyan S, Weinberg RA. 2011. Tumor metastasis: molecular insights and evolving paradigms. Cell, 147 (2): 275–292.
  • Verma N, Kaur G. 2016. Trends on Biosensing Systems for Heavy Metal Detection. In Comprehensive Analytical Chemistry, Elsevier: Amsterdam, The Netherlands, Volume 74, pp. 33–71, ISBN 978-0-444-63579-2.
  • Vu T, Claret FX. 2012. Trastuzumab: updated mechanisms of action and resistance in breast cancer. Front. Oncol., 2: 62.
  • Way JC, Collins JJ, Keasling JD, Silver PA. 2014. Integrating biological redesign: Where synthetic biology came from and where it needs to go. Cell, 157: 151–161.
  • Weng X, Neethirajan S. 2017. Ensuring food safety: Quality monitoring using microfluidics. Trends Food Sci. Technol., 65: 10–22.
  • Xiao Y, Lubin AA, Heeger AJ, Plaxco KW. 2005. Label-free electronic detection of thrombin in blood serum by using an aptamer-based sensor. Angew. Chem. Int. Ed. Engl., 44: 5456–5459.
  • Yildirim N, Long F, He M, Shi HC, Gu AZ. 2014. A portable optic fiber aptasensor for sensitive, specific and rapid detection of bisphenol-A in water samples. Environ. Sci. Process Impacts, 16: 1379–1386.
  • Yoshida K, Miki Y. 2004. Role of BRCA1 and BRCA2 as regulators of DNA repair, transcription, and cell cycle in response to DNA damage. Cancer Sci., 95 (11): 866–871.
  • Zhang D, Lu Y, Zhang Q, et al. 2015. Nanoplasmonic monitoring of odorants binding to olfactory proteins from honeybee as biosensor for chemical detection. Sens. Actuators B Chem., 221: 341–349.
  • Zhang F, Zhang Q, Zhang D, Lu Y, Liu Q, Wang P. 2014. Biosensor analysis of natural and artificial sweeteners in intact taste epithelium. Biosens. Bioelectron., 54: 385–392.
  • Zhang W, Asiri AM, Liu D, Du D, Lin Y. 2015. Nanomaterial-based biosensors for environmental and biological monitoring of organophosphorus pesticides and nerve agents. Trends Anal. Chem., 54: 1–10.