Biosensor Array Research Articles

A Multi-Functional CMOS Biosensor Array With On-Chip DEP-Assisted Sensing for Rapid Low-Concentration Analyte Detection and Close-Loop Particle Manipulation With No External Electrodes.

This article presents a fully-integrated dielectrophoresis (DEP)-assisted multi-functional CMOS biosensor array chip with 4096 working electrodes (WEs), 12288 photodiodes (PDs), reference electrodes (REs), and counter electrodes (CEs), while each WE and photodiode can be reconfigured to support on-chip DEP actuation, electrochemical potentiostat, optical shadow imaging, and complex impedance sensing. The proposed CMOS biosensor is an example of an actuation-assisted label-free biosensor for the rapid sensing of low-concentration analytes. The DEP actuator of the proposed CMOS biosensor does not require any external electrode. Instead, on-chip WE pairs can be re-used for DEP actuation to simplify the sensor array design. The CMOS biosensor is implemented in a standard 130-nm BiCMOS process. Theoretical analyses and finite element method (FEM) simulations of the on-chip DEP operations are conducted as proof of concept. Biological assay measurements (DEP actuation/electrochemical potentiostat/impedance sensing) with E.coli bacteria and microbeads (optical shadow imaging) demonstrate rapid detection of low-concentration analytes and simultaneous manipulation and detection of large particles. The on-chip DEP operations draw the analytes closer to the sensor electrode surface, which overcomes the diffusion limit and accelerates low-concentration analyte sensing. Moreover, the DEP-based movement of large particles can be readily detected by on-chip photodiode arrays to achieve close-loop manipulation and sensing of particles and droplets. These show the unique advantages of the DEP-assisted multi-functional biosensor.

A universal dual-mode hydrogel array based on phage-DNA probe for simultaneous rapid screening and precisely quantitative detection of Escherichia coli O157:H7 in foods by the fluorescent/microfluidic chip electrophoresis methods

Rapid and specific detection of virulent bacterial strains is a great challenge for food safety regarding large amounts of contaminated samples. Herein, a dual-mode hydrogel array biosensor was constructed to simultaneously rapidly screen and precisely quantitatively detect virulent Escherichia coli O157:H7 (E. coli O157:H7) based on a novel DNA-modified phage probe. First, E. coli O157:H7 was incubated with alginate to form the E. coli O157:H7/hydrogel premix complex. Subsequently, hydrogel formation by cross-linking upon the addition of calcium ions and phages for E. coli O157:H7 modified with a DNA primer (phage-DNA) was added to the alginate hydrogel. The DNA on the complex could trigger rolling circle amplification (RCA) to form a phage probe containing a long-chain DNA skeleton (phage@RCA-DNA). The RCA-DNA was then hybridized with the complementary DNA (cDNA) to form double-stranded DNA fragments (phage@RCA-dsDNA), which could be stained by the SYBR Green dye to emit visual green fluorescence (FL) and determined by a smartphone for rapid screening. Meanwhile, the unreacted cDNA in the supernatant could be quantitatively detected by microfluidic chip electrophoresis (MCE). The signal decrement was also proportional to the bacterial concentration. The detection limit values of E. coli O157:H7 were 50 CFU mL−1 by the FL signal and 6 CFU mL−1 by the MCE signal. The two results could be mutually corrected to decrease the false-positive results. This assay was also employed to detect virulent Salmonella Typhimurium (S. Typhimurium) using the corresponding S. Typhimurium phage@RCA-DNA probe. All these results demonstrated that the universal bioassay was suitable for simultaneous rapid screening and precisely quantitative detection of virulent bacterial strains.

Direct Writing of Aligned Carbon Nanotubes across a Trench.

Aligned and suspended carbon nanotubes can outperform randomly oriented networks in electronic biosensing and thin-film electronics. However, carbon nanotubes tend to bundle and form random networks. Here, we show that carbon nanotubes spontaneously align in an ammonium deoxycholate surfactant gel even under low shear forces, allowing direct writing and printing of nanotubes into electrically conducting wires and aligned thin layers across trenches. To demonstrate its application potential, we directly printed arrays of disposable electrical biosensors, which show femtomolar sensitivity in the detection of DNA and SARS-CoV-2 RNA.

Analysis of Capacitance Variation with Pattern Size for Multi-well Array Biosensor: Study of Cell Behavior with the ECIS System

Analysis of Capacitance Variation with Pattern Size for Multi-well Array Biosensor: Study of Cell Behavior with the ECIS System

Lactation physiokinetics-using advances in technology for a fresh perspective on human milk transfer.

Though the nature of breastfeeding is critical, scant information is available on how the action of the milk transfer from mother to infant is regulated in humans, where the points of dysfunction are, and what can be done to optimize breastfeeding outcomes. While better therapeutic strategies are needed, before they can be devised, a basic scientific understanding of the biomechanical mechanisms that regulate human milk transfer from breast to stomach must first be identified, defined, and understood. Combining systems biology and systems medicine into a conceptual framework, using engineering design principles, this work investigates the use of biosensors to characterize human milk flow from the breast to the infant's stomach to identify points of regulation. This exploratory study used this framework to characterize Maternal/Infant Lactation physioKinetics (MILK) utilizing a Biosensor ARray (BAR) as a data collection method. Participants tolerated the MILKBAR well during data collection. Changes in breast turgor and temperature were significant and related to the volume of milk transferred from the breast. The total milk volume transferred was evaluated in relation to contact force, oral pressure, and jaw movement. Contact force was correlated with milk flow. Oral pressure appears to be a redundant measure and reflective of jaw movements. Nipple and breast turgor, jaw movement, and swallowing were associated with the mass of milk transferred to the infant's stomach. More investigation is needed to better quantify the mass of milk transferred in relation to each variable and understand how each variable regulates milk transfer.

Electrochemical Biosensor Arrays for Multiple Analyte Detection

AbstractThe simultaneous detection of multiple analytes using electrochemical biosensor arrays has demonstrated significant potential in various fields, including medical diagnostics. These platforms are designed to be low‐cost, easy to use, and offer fast detection of a range of molecules. This concept article discusses the components necessary to achieve multiplexing with electrochemical biosensor arrays. The various methods used to fabricate electrode arrays of different types are discussed. Furthermore, the methods for the selective immobilization of multiple different bioreceptors onto individual electrodes within the array, a crucial step essential for conferring specificity to the analytical processes, are presented with relevant examples. We have focused on enzymes, antibodies and aptamers as examples of bioreceptors that have been deployed in various multianalyte electrochemical detection platforms. Finally, we discuss the key challenges associated with their application for the analysis of real samples and provide a future outlook on possible strategies that can be used to overcome these challenges.

Hydrogel-enzyme micropatch array format for chemical mapping: A proof of concept

Conventional sensing methods report on concentrations of analytes in a single point of sampled medium or provide an average value. However, distributions of substances on surfaces of sampled objects often exhibit intricate inhomogeneities. In order to obtain snapshots of the chemical distributions on surfaces, we have developed enzyme-loaded hydrogel arrays (5 × 5 and 10 × 10). The acrylic 10 × 10 array base contains 100 holes, which are filled with agarose hydrogel containing assay enzymes and substrates. Such arrays can be exposed to the analyzed surfaces to collect minute amounts of analytes. Following a brief incubation, they are subsequently visualized in a custom-built array reader device. The reader incorporates a light-emitting diode-based light source, miniature camera, and Raspberry Pi single-board computer. Two Python programs capture and analyze the images of the array to extract pixel saturation values corresponding to individual hydrogel micropatches. The method has been thoroughly optimized for mapping of glucose and lactic acid. The optimized parameters were: contact time, agarose concentration, substrate concentration, enzyme concentration ratio, and enzyme concentration. The array biosensor was further tested by mapping glucose distribution in fruit/vegetable cross-sections (apple, guava, and cucumber) and lactic acid distribution in cheese. We think that this new hydrogel-based chemical mapping method can find applications in studies related to food science, plant physiology, clinical chemistry, and forensics; wherever the distributions of analytes on the tested surfaces need to be assessed.

Linking aberrant glycosylation of plasma glycoproteins with progression of myelodysplastic syndromes: a study based on plasmonic biosensor and lectin array

Aberrant glycosylation of glycoproteins has been linked with various pathologies. Therefore, understanding the relationship between aberrant glycosylation patterns and the onset and progression of the disease is an important research goal that may provide insights into cancer diagnosis and new therapy development. In this study, we use a surface plasmon resonance imaging biosensor and a lectin array to investigate aberrant glycosylation patterns associated with oncohematological disease—myelodysplastic syndromes (MDS). In particular, we detected the interaction between the lectins and glycoproteins present in the blood plasma of patients (three MDS subgroups with different risks of progression to acute myeloid leukemia (AML) and AML patients) and healthy controls. The interaction with lectins from Aleuria aurantia (AAL) and Erythrina cristagalli was more pronounced for plasma samples of the MDS and AML patients, and there was a significant difference between the sensor response to the interaction of AAL with blood plasma from low and medium-risk MDS patients and healthy controls. Our data also suggest that progression from MDS to AML is accompanied by sialylation of glycoproteins and increased levels of truncated O-glycans and that the number of lectins that allow discriminating different stages of disease increases as the disease progresses.

Application of magnetic-nanoparticle functionalized whole-cell biosensor array for bioavailability and ecotoxicity estimation at urban contaminated sites

The bioavailability and ecotoxicity of pollutants are important for urban ecological systems and human health, particularly at contaminated urban sites. Therefore, whole-cell bioreporters are used in many studies to assess the risks of priority chemicals; however, their application is restricted by low throughput for specific compounds and complicated operations for field tests. In this study, an assembly technology for manufacturing Acinetobacter-based biosensor arrays using magnetic nanoparticle functionalization was developed to solve this problem. The bioreporter cells maintained high viability, sensitivity, and specificity in sensing 28 priority chemicals, seven heavy metals, and seven inorganic compounds in a high-throughput manner, and their performance remained acceptable for at least 20 d. We also tested the performance by assessing 22 real environmental soil samples from urban areas in China, and our results showed positive correlations between the biosensor estimation and chemical analysis. Our findings prove the feasibility of the magnetic nanoparticle-functionalized biosensor array to recognize the types and toxicities of multiple contaminants for online environmental monitoring at contaminated sites.

A multi-unit integrated electrochemical biosensor array for synergistic signal enhancing carbohydrate antigen 125 detection

Significant progress has been made in recent decades; however, the development of an accurate, portability and high-throughput electrochemical biosensor for quantifying trace biomarker in complex biological samples remains challenging. In this study, we described a novel 3 × 3 multi-unit portable integrated biosensor array, specifically designed for parallel and precise detection of trace levels of carbohydrate antigen 125 (CA-125) using multiplex synergistic signal amplification. The sensor array substrate was constructed on a planar printed circuit board (PCB) using printing technology, making them integrated, portable, affordable and disposable. The exceptional sensitivity of the biosensor is attributed to the nitrogen-doped mesoporous carbon (NMC) nanomaterial, which possesses a large surface area, superior conductivity and tunable pore size, enabling high affinity of and enzyme catalytic activity. The integrated biosensing array platform consists of individually controlled sensors, allowing for high-throughput tests of the same sample simultaneously, ensuring the reliability and accuracy of assay. The developed biosensor array system demonstrated excellent sensitivity and rapid CA-125 assay, achieving an impressive detection limit as low as 0.027 U/mL (S/N = 3). Meanwhile, the high-throughput multiplex test results (n = 9) were obtained within a short timeframe of 30 min. Ultimately, the biosensor array successfully quantified CA-125 in human serum, yielding results comparable to the enzyme–linked immunosorbent assay technique. This technology presents a highly promising strategy that can be potentially extended to detect other biomarkers for biological analysis and early disease diagnosis.

Dual-parameter cell biosensor for real-time monitoring of effects of propionic acid on neurons.

Currently, only a few small devices are capable of continuously recording the physiological states of neurons in real time. Micro-electrode arrays (MEAs) are widely used as electrophysiological technology to detect the excitability of neurons non-invasively. However, the development of miniaturized and multi-parameter MEAs capable of real-time recording remains challenging. In this study, an on-chip micro-electrode and platinum resistor array (MEPRA) biosensor was designed and fabricated to monitor both the electrical and temperature signals of cells synchronously in real time. Such on-chip sensor maintains high sensitivity and stability. The MEPRA biosensor was further used to investigate the effects of propionic acid (PA) on primary neurons. The results demonstrate that PA affects the temperature and firing frequency of primary cortical neurons in concentration-dependent manners. The changes of temperature and firing frequency work in tandem with neuronal physiological status, including neuron viability, intracellular calcium concentration, neural plasticity, and mitochondrial function. This highly biocompatible, stable, and sensitive MEPRA biosensor may provide high-precision reference information for investigating the physiological responses of neuron cells under various conditions.

Water‐Based Conductive Ink Formulations for Enzyme‐Based Wearable Biosensors

AbstractHerein, this work reports the first example of second‐generation wearable biosensor arrays based on a printed electrode technology involving a water‐based graphite ink, for the simultaneous detection of l‐lactate and d‐glucose. The water‐based graphite ink is deposited onto a flexible polyethylene terephthalate sheet, namely stencil‐printed graphite (SPG) electrodes, and further modified with [Os(bpy)2(Cl)(PVI)10] as an osmium redox polymer to shuttle the electrons from the redox center of lactate oxidase from Aerococcus viridans (LOx) and gluocose oxidase from Aspergillus niger (GOx). The proposed biosensor array exhibits a limit of detection as low as (9.0 ± 1.0) × 10−6 m for LOx/SPG‐[Os(bpy)2(Cl)(PVI)10] and (3.0 ± 0.5) × 10−6 m for GOx/SPG‐[Os(bpy)2(Cl)(PVI)10], a sensitivity as high as 1.32 μA mm−1 for LOx/SPG‐[Os(bpy)2(Cl)(PVI)10] and 28.4 μA mm−1 for GOx/SPG‐[Os(bpy)2(Cl)(PVI)10]. The technology is also selective when tested in buffer and artificial sweat and is endowed with an operational/storage stability of ≈80% of the initial signal retained after 20 days. Finally, the proposed array is integrated in a wristband and successfully tested for the continuous monitoring of l‐lactate and d‐glucose in a healthy volunteer during daily activity. This is foreseen as a real‐time wearable device for sport‐medicine and healthcare applications.

CRISPR-Cas12a Biosensor Array for Ultrasensitive Detection of Unamplified DNA with Single-Nucleotide Polymorphic Discrimination

Quantitative polymerase chain reaction as a powerful tool for DNA detection has been pivotal to a vast range of applications, including disease screening, food safety assessment, environmental monitoring, and many others. However, the essential target amplification step in combination with fluorescence readout poses a significant challenge to rapid and streamlined analysis. The discovery and engineering of the clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated (Cas) technology have recently paved the way for a novel approach to nucleic acid detection, but the majority of current CRISPR-mediated DNA detection platforms are limited by insufficient sensitivity and still require target preamplification. Herein, we report a CRISPR-Cas12a-mediated graphene field-effect transistor (gFET) array, named CRISPR Cas12a-gFET, for amplification-free, ultrasensitive, and reliable detection of both single-stranded DNA (ssDNA) and double-stranded DNA (dsDNA) targets. CRISPR Cas12a-gFET leverages the multiturnover trans-cleavage activity of CRISPR Cas12a for intrinsic signal amplification and ultrasensitivity of gFET. As demonstrated, CRISPR Cas12a-gFET achieves a limit of detection of 1 aM for the ssDNA human papillomavirus 16 synthetic target and 10 aM for the dsDNA Escherichia coli plasmid target without target preamplification. In addition, an array of 48 sensors on a single 1.5 cm × 1.5 cm chip is employed to improve data reliability. Finally, Cas12a-gFET demonstrates the capability to discriminate single-nucleotide polymorphisms. Together, the CRISPR Cas12a-gFET biosensor array provides a detection tool for amplification-free, ultrasensitive, reliable, and highly specific DNA detections.

3D printing for customized carbon electrodes.

Traditional carbon electrodes are made of glassy carbon or carbon fibers and have limited shapes. 3D printing offers many advantages for manufacturing carbon electrodes, such as complete customization of the shape and the ability to fabricate devices and electrodes simultaneously. Additive manufacturing is the most common 3D printing method, where carbon materials are added to the material to make it conductive, and treatments applied to enhance electrochemical activity. A newer form of 3D printing is 2-photon lithography, where electrodes are printed in photoresist via laser lithography and then annealed to carbon by pyrolysis. Applications of 3D printed carbon electrodes include nanoelectrode measurements of neurotransmitters, arrays of biosensors, and integrated electrodes in microfluidic devices.

Study of reaction-diffusion controlled mass transport in stopped-flow fluidics for spatiotemporal multiplexing

Integration of biochemical reaction networks (BRNs) with biosensor platforms has emerged as a technological niche overcoming challenges related to the loss of sensitivity and selectivity in biological media. Optimal operation of BRNs in microfluidics requires control over reaction-diffusion dominated mass transport, heavily influenced by fluidic parameters. In this work, we study and design an on-chip platform combining a programable unique molecular amplification as BRNs with nanoscale biologically sensitive field-effect transistor (BioFET) arrays, which employs a physical diffusion barrier to gain spatial and temporal control over mass transport. Computational and numerical approaches, such as finite element and finite volume methods, were implemented to solve partial differential equations numerically after domain approximation by numerous finite elements. The focus on geometrical optimizations of fluidics is aimed at mass transport to occur with precise spatial and temporal control toward BioFET-arrays. Adopting a 0.5 pM limit-of-detection (LoD) for biochemical monitoring of BRNs via a single-stranded deoxyribonucleic acid (ssDNA) output, we show that it was possible to compartmentalize the mass transport spatiotemporally without crosstalk, which can be of critical advantage for using biosensor arrays in order to realize simplified multiplexed point-of-care biosensors.

A stretchable wireless wearable bioelectronic system for multiplexed monitoring and combination treatment of infected chronic wounds.

Chronic nonhealing wounds are one of the major and rapidly growing clinical complications all over the world. Current therapies frequently require emergent surgical interventions, while abuse and misapplication of therapeutic drugs often lead to an increased morbidity and mortality rate. Here, we introduce a wearable bioelectronic system that wirelessly and continuously monitors the physiological conditions of the wound bed via a custom-developed multiplexed multimodal electrochemical biosensor array and performs noninvasive combination therapy through controlled anti-inflammatory antimicrobial treatment and electrically stimulated tissue regeneration. The wearable patch is fully biocompatible, mechanically flexible, stretchable, and can conformally adhere to the skin wound throughout the entire healing process. Real-time metabolic and inflammatory monitoring in a series of preclinical in vivo experiments showed high accuracy and electrochemical stability of the wearable patch for multiplexed spatial and temporal wound biomarker analysis. The combination therapy enabled substantially accelerated cutaneous chronic wound healing in a rodent model.

Dual Functional Full-Color Carbon Dot-Based Organelle Biosensor Array for Visualization of Lipid Droplet Subgroups with Varying Lipid Composition in Living Cells.

In situ visualization of lipid composition diversity in lipid droplets (LDs) is essential for decoding lipid metabolism and function. However, effective probes for simultaneously localizing and reflecting the lipid composition of LDs are currently lacking. Here, we synthesized full-color bifunctional carbon dots (CDs) that can target LDs as well as respond to the nuance in internal lipid compositions with highly sensitive fluorescence signals, due to lipophilicity and surface state luminescence. Combined with microscopic imaging, uniform manifold approximation and projection, and sensor array concept, the capacity of cells to produce and maintain LD subgroups with varying lipid composition was clarified. Moreover, in oxidative stress cells, LDs with characteristic lipid compositions were deployed around mitochondria, and the proportion of LD subgroups changed, which gradually disappeared when treated with oxidative stress therapeutics. The CDs demonstrate great potential for in situ investigation of the LD subgroups and metabolic regulations.

Accurate and non-destructive monitoring of mold contamination in foodstuffs based on whole-cell biosensor array coupling with machine-learning prediction models

Mold contamination in foodstuffs causes huge economic losses, quality deterioration and mycotoxin production. Thus, non-destructive and accurate monitoring of mold occurrence in foodstuffs is highly required. We proposed a novel whole-cell biosensor array to monitor pre-mold events in foodstuffs. Firstly, 3 volatile markers ethyl propionate, 1-methyl-1 H-pyrrole and 2,3-butanediol were identified from pre-mold peanuts using gas chromatography-mass spectrometry. Together with other 3 frequently-reported volatiles from Aspergillus flavus infection, the volatiles at subinhibitory concentrations induced significant but differential response patterns from 14 stress-responsive Escherichia coli promoters. Subsequently, a whole-cell biosensor array based on the 14 promoters was constructed after whole-cell immobilization in calcium alginate. To discriminate the response patterns of the whole-cell biosensor array to mold-contaminated foodstuffs, optimal classifiers were determined by comparing 6 machine-learning algorithms. 100 % accuracy was achieved to discriminate healthy from moldy peanuts and maize, and 95 % and 98 % accuracy in discriminating pre-mold stages for infected peanuts and maize, based on random forest classifiers. 83 % accuracy was obtained to separate moldy peanuts from moldy maize by sparse partial least square determination analysis. The results demonstrated high accuracy and practicality of our method based on a whole-cell biosensor array coupling with machine-learning classifiers for mold monitoring in foodstuffs.

Visualization analysis of glucose, lactate and cholesterol based on an electrochemiluminescent biosensor array

Visualization analysis of glucose, lactate and cholesterol based on an electrochemiluminescent biosensor array

Pushing Differential Sensing Further: The Next Steps in Design and Analysis of Bio‐Inspired Cross‐Reactive Arrays

AbstractDifferential sensing is a technique that uses an array of cross‐reactive receptors to create a unique fingerprint to detect analytes. Over the past two decades significant progress in the field has highlighted the power of this approach, enabling detection with commercially available or synthetically simple sensors, discrimination of structurally similar and challenging analytes, and low concentration detection. In this Concept paper, we briefly review developments in the field and highlight areas for future exploration. We believe there is still much room to grow, particularly in designing biosensor arrays, achieving simultaneous quantification of multiple analytes (i. e., multiplexing), and implementation of more advanced machine learning algorithms in array response analysis.