DNA-Based Biosensors for the Biochemical Analysis: A Review

Photo-controlled cascade DNA hybridization for amplified electrochemical biosensor with tunable sensing performance

BACKGROUND

Precise control of the biorecognition process in DNA biosensors, especially for those with signal amplification, remains a challenge. It is of great significance to introduce external stimuli into the DNA system for a controllable trigger of nucleic acid cascade amplification and further for excellent biosensors.

RESULTS

In this study, a photo-initiated hybridization chain reaction (HCR) was designed for controllable and sensitive electrochemical biosensor via the incorporation of azobenzene moiety into the assembly unit. Under the coexistence of UV light and target DNA, a number of HCR products with biotin tags were generated and fixed on the electrode surface. Subsequently, the bound streptavidin-labeled horseradish peroxidase (SA-HRP) effectively catalyzed H2O2-mediated oxidation of tetramethylbenzidine (TMB), producing significant electrochemical current signals. A tunable sensing performance with different dynamic response ranges and sensitivity was achieved by adjusting the number of the inserted azobenzene moieties and the control of UV light. A limit of detection as low as 2.5 fM (S/N = 3) could be obtained in the case of one azobenzene and under UV exposure. Moreover, the photo-controlled DNA biosensor exhibited good discrimination ability even against single-base mismatch and was able to be applied in serum samples.

SIGNIFICANCE

The proposed electrochemical DNA biosensor based on dual-triggered HCR amplification may represent a promising path to achieve sensitive and accurate bioanalysis. Also, the tunable dynamic range of the developed biosensor will provide the possibility of clinical applications.

Tailoring DNA Surface Interactions on Single-Layer Graphene: Comparative Analysis of Pyrene, Acridine, and Fluorenyl Methyl Linkers

This study investigates the effect of different linkers and solvents on the immobilization of DNA probes on graphene surfaces, which are crucial for developing high-performance biosensors. Quartz crystal microbalance with dissipation (QCM-D) measurements were used to characterize in situ and real-time the immobilization of ssDNA and hybridization efficiency on model graphene surfaces. The DNA probes immobilization kinetics and thermodynamics were systematically investigated for all the pairings between three bifunctional linkers─1-pyrenebutyric acid succinimidyl ester (PBSE), Fluorenylmethylsuccinimidyl carbonate (FSC), and Acridine Orange (AO) succinimidyl ester─and three organic solvents (DMF, DMSO, and 10% DMF/ethanol). The linker's spatial orientation and effective surface modification for DNA probe attachment were also evaluated based on footprints and DNA probe surface coverage. Graphene surfaces functionalized with PBSE in DMF achieved the highest DNA probe surface density (up to 1.31 × 1013 molecules cm-2) and fastest kinetic, p values above 4, and hybridization efficiencies of at least 70%, with 20 to 30% of ssDNA directly adsorbed nonspecifically on the functionalized graphene surface, which has significant implications for the design of sensitive biosensors. The efficiency of the ethanolamine-NHS blocking reaction was estimated to be 80%. The surface packing density of the linker was estimated at 25% of the entire surface coverage for PBSE, and about 22 and 13% for AO and FSC, respectively. Overall, the surface coverage achieved for probe DNA was in the same order of magnitude as that obtained on flat gold surfaces (≥1013 molecules cm-2), typically used in biosensors. These findings highlight the importance of the selected conditions for graphene surface modification to achieve high DNA probe surface density on graphene materials. These results underscore the critical role of interface engineering in achieving target functional outcomes in biosensing technology.

Recent Advances in Biosensors Based on Hybridization Chain Reaction and Silver Nanoclusters

Hybridization chain reaction (HCR) and DNA-templated silver nanoclusters (AgNCs) have emerged as powerful tools in biosensing. HCR enables cascade amplification through programmable DNA interactions, while DNA-AgNCs serve as transducing units with unique fluorogenic and electrochemical properties. Integrating these components into a hybrid sensor could significantly enhance sensing capabilities across various fields. Nonetheless, limited studies and the lack of systematic guidelines for HCR-AgNCs systems have hindered research progress, despite their potential. This review aims to address this gap by providing a comprehensive overview of HCR-AgNCs biosensors, facilitating further innovation in this field. The working principles, performance factors, and complementary features are discussed. Thereafter, reported HCR-AgNCs studies are assessed, emphasizing their distinct sensing mechanisms (e.g., fluorogenic, electrochemical), applications across various fields, and challenges in adopting the hybrid sensors. Drawing from the experience developing multiple HCR-AgNCs sensors, insights and guidelines for designing and developing HCR-AgNCs systems are provided for future researchers. Finally, prospective directions in HCR-AgNCs research, including multiplex assays and integration with emerging technologies, are explored to guide future advancements. The synergistic combination of HCR and AgNCs as a hybrid biosensor holds promise for addressing pressing challenges in healthcare, environmental monitoring, and beyond, paving the way for next-generation biosensing technologies.

Transfer learning Bayesian optimization for competitor DNA molecule design for use in diagnostic assays

With the rise in engineered biomolecular devices, there is an increased need for tailor-made biological sequences. Often, many similar biological sequences need to be made for a specific application meaning numerous, sometimes prohibitively expensive, lab experiments are necessary for their optimization. This paper presents a transfer learning design of experiments workflow to make this development feasible. By combining a transfer learning surrogate model with Bayesian optimization, we show how the total number of experiments can be reduced by sharing information between optimization tasks. We demonstrate the reduction in the number of experiments using data from the development of DNA competitors for use in an amplification-based diagnostic assay. We use cross-validation to compare the predictive accuracy of different transfer learning models, and then compare the performance of the models for both single objective and penalized optimization tasks.

Trends of Nanobiosensors in Modern Agriculture Systems

Sustainable agriculture and the provision of food for all become dependent on the availability of efficient diagnostic techniques for the prompt identification of plant diseases. Current scientific findings suggest that nanotechnology can positively affect the agrifood industry by reducing the adverse effects of agricultural practices on human health and the environment, increasing food security and productivity, and fostering social and economic justice. Nanomaterials' unique physical and chemical characteristics have made it possible to employ them as cutting-edge, effective diagnostic instruments for various plant infections and other significant disease biomarkers. By creating diagnostic instruments and methods, nanobiosensors significantly contribute to the revolution of farming. In real time, nanobiosensors can detect infections, metabolites, pesticides, nutrient levels, soil moisture, and temperature. This helps with precision farming techniques and maximises resource use. To better address agricultural concerns, we have included the most recent research on the concept, types, applications, commercial aspects, and future scope of nanobiosensors in this review.

Development of a Molecular Beacon-Based Genosensor for Detection of Human Rotavirus A

The rotavirus-led fatal infantile gastroenteritis in the globe demands a portable, specific, and low-cost diagnostic tool for its timely detection and effective surveillance in a mass population. Consequently, the design and development of an advanced biosensing technique for its detection is of paramount importance. A highly conserved 23-nucleotide sequence, 5' GCTAGGGATAAGATTGTTGAAGG 3', was identified by a human rotavirus A VP6 gene sequence analysis and designated as the target. A molecular beacon of 33 nucleotides was designed with the sequence 5'[Fluorescein] ATAGTCCTTCAACAATCTTATCCCTAGCACTAT[Dabcyl]3', incorporating stem and loop regions. Secondary and tertiary structure characterizations confirmed the desired stem-loop structure without internal secondary structures. The thermal stability of the molecular beacon-target complex was studied using a temperature vs. Gibbs free energy change plot, melting curve analysis based on absorbance vs. temperature, and an experimental fluorescence resonance energy transfer melting assay. The melting temperature of the molecular beacon-target complex was experimentally determined to be 62 °C. The spectral analysis showed fluorescence restoration in the presence of the synthetic VP6 target. The assay conditions were optimized with an excitation wavelength of 470 nm and a 10-min incubation time. The assay demonstrated a linear correlation between fluorescence intensity restoration and target concentration, with a limit of detection of 18.8 nM. Interference studies with single mismatch, double mismatch, and scrambled targets revealed that the molecular beacon has strong specificity for the VP6 target, effectively discriminating against non-target sequences. This work demonstrates the molecular beacon's potential as a sensitive and specific tool for detecting rotavirus A VP6 gene, with promising applications in diagnostic assays for the rotavirus disease management.

The role of DNA nanotechnology in medical sensing

This paper explores how DNA nanotechnology enhances biosensors in medicine and pharmacology by taking advantage of the unique characteristics of DNA and the unique advantages of DNA origami technology. DNA origami allows the establishment of complex nanoobjects with precise size and complete molecular writability as well as the possibility of seamless integration and biocompatibility with biological systems. Utilizing this, the chemical denaturation of DNA chains allows for the combination of various functions, including organic fluorescence groups and photoreaction elements, etc. This has allowed DNA origami to become a transformative tool in biotechnology and other fields because of its versatility, use in innovative applications improving the design and function of biosensors, and potential to provide greater possibilities for early disease diagnosis and personalized medicine.

Development of a Novel Colorimetric pH Biosensor Based on A-Motif Structures for Rapid Food Freshness Monitoring and Spoilage Detection

Accurate methods for assessing food freshness through colorimetric pH response play a critical role in determining food spoilage and ensuring food quality standards. This study introduces a novel unlabeled DNA sequence, poly-dA20, designed to exploit the colorimetric properties of both the single strand and the fold-back A-motif structure in conjunction with gold nanoparticles (AuNPs) under varying pH conditions. When exposed to storage temperatures of 4 °C and 25 °C, the color variations in the AuNP solution, influenced by pH level changes in mutton and sea bass samples' different storage periods, are easily discernible to the naked eye within a minute. The ratio of UV absorption values at 527 nm and 700 nm (A527/A700) demonstrates a strong linear correlation with both the storage duration and pH of the food samples. Furthermore, a comprehensive analysis combining the total volatile basic nitrogen (TVB-N) value with the A527/A700 ratio is employed for precise assessment of food freshness. The innovative pH-responsive sensing strategy not only provides a new approach for on-site food freshness and spoilage detection systems but also serves as a valuable tool for pH-related biological detection in clinical diagnostic applications.

Bifunctional Protein TC1 Mediated One-Pot Strategy for Robust Immobilization of DNA with High Accessibility

Immobilizing DNA with high accessibility at the interface is attractive but challenging. Current methods often involve multiple chemical reactions and derivatives. In this study, an endonuclease, TC1, is introduced to develop a robust strategy for immobilizing DNA with enhanced accessibility. TC1 enables direct immobilization of DNA onto a solid support through self-catalytic DNA covalent coupling and robust solid adsorption capabilities. This method demonstrates high accessibility to target molecules, supported by the improved sensitivity of DNA hybridization and aptamer-target recognition assays. TC1-mediated DNA immobilization is a one-pot reaction that does not require chemical derivatives, making it promising for the development of high-performance DNA materials and technologies.

Transfer Learning Bayesian Optimization to Design Competitor DNA Molecules for Use in Diagnostic Assays

With the rise in engineered biomolecular devices, there is an increased need for tailor-made biological sequences. Often, many similar biological sequences need to be made for a specific application meaning numerous, sometimes prohibitively expensive, lab experiments are necessary for their optimization. This paper presents a transfer learning design of experiments workflow to make this development feasible. By combining a transfer learning surrogate model with Bayesian optimization, we show how the total number of experiments can be reduced by sharing information between optimization tasks. We demonstrate the reduction in the number of experiments using data from the development of DNA competitors for use in an amplification-based diagnostic assay. We use cross-validation to compare the predictive accuracy of different transfer learning models, and then compare the performance of the models for both single objective and penalized optimization tasks.

DNA-Based Complexes and Composites: A Review of Fabrication Methods, Properties, and Applications

Deoxyribonucleic acid (DNA), a macromolecule that stores genetic information in organisms, has recently been gradually developed into a building block for new materials due to its stable chemical structure and excellent biocompatibility. The efficient preparation and functional integration of various molecular complexes and composite materials based on nucleic acid skeletons have been successfully achieved. These versatile materials possess excellent physical and chemical properties inherent to certain inorganic or organic molecules but are endowed with specific physiological functions by nucleic acids, demonstrating unique advantages and potential applications in materials science, nanotechnology, and biomedical engineering in recent years. However, issues such as the production cost, biological stability, and potential immunogenicity of DNA have presented some unprecedented challenges to the application of these materials in the field. This review summarizes the cutting-edge manufacturing techniques and unique properties of DNA-based complexes and composites and discusses the trends, challenges, and opportunities for the future development of nucleic acid-based materials.

Multi-functional imidazolium dendrimers based on thiacalix[4]arenes: self-assembly, catalysis and DNA binding

For the first time, dendrimers based on thiacalix[4]arenes bearing imidazolium dendrons on one side and alkyl fragments on another side of the macrocyclic platform and symmetrical dendrimers with four dendrons on both sides were synthesized. Dendrons consist of gallic acid-based branches functionalized with imidazolium and triazolium groups. The physicochemical properties of the dendrimers such as micellar concentration (CMC), size, and solubilization capacity were measured. Novel dendrimers exhibit high binding efficiency with calf thymus DNA (ctDNA) as revealed by fluorescence quenching of the DNA-EtBr complex in the presence of macrocycles. Dendrimers have been used as supports for Pd nanoparticles, which show high catalytic activity for the reduction of nitroaromatic compounds.

Enhancing early warning: A DNA biosensor with polyaniline/graphene nanocomposite for label-free voltammetric detection of saxitoxin-producing harmful algae

Yearly reports of detrimental effects resulting from harmful algal blooms (HAB) are still received in Malaysia and other countries, particularly concerning fish mortality and seafood contamination, both of which bear consequences for the fisheries industry. The underlying reason is the absence of a dependable early warning system. Hence, this research aims to develop a single DNA biosensor that can detect a group of HAB species known for producing saxitoxin (SXT), which is commonly found in Malaysian waters. The screen-printed carbon electrode (SPCE)-based DNA biosensor was fabricated by covalent grafting of the 3' aminated DNA probe of the sxtA4 conserved domain in SXT-producing dinoflagellates on the reverse-phase polymerized polyaniline/graphene (PGN) nanocomposite electrode via carbodiimide linkage. The introduction of a carboxyphenyl layer to the PGN nanotransducing element was essential to augment the carboxylic groups on the graphene (RGO), facilitating attachment with the aminated DNA. The synergistic effect of the asynthesized nanocomposite of PANI and RGO, tremendously enhanced the electron transfer rate of the ferri/ferrocyanide redox probe at the SPCE transducer surface, allowing for the label-free bioanalytical assay of complementary DNA targets. The developed DNA biosensor featuring the capacity to detect a broad range of Alexandrium minutum (A. minutum) cell concentrations, ranging from 10 to 10,000,000 cells L-1. The quantification of A. minutum cells from pure algal culture by the electrochemical DNA biosensor has been well-validated with traditional microscopic techniques. Furthermore, Alexandrium tamiyavanichii, another toxigenic HAB species, exhibited a similar electrochemical characteristic signal to those observed with A. minutum, whilst the biosensor yielded appreciably distinctive results when subjected to a non-toxigenic microalgae species as a negative control, i.e. Isochrysis galbana. A compendium DNA biosensor design and electrochemical detection strategy at laboratory scale serves as a precursor to the potential development of portable device for on-site detection, thus expanding the utility and scope of biosensor technology.

CRISPR-Based Biosensors for Medical Diagnosis: Readout from Detector-Dependence Detection Toward Naked Eye Detection

The detection of biomarkers (such as DNA, RNA, and protein) plays a vital role in medical diagnosis. The CRISPR-based biosensors utilize the CRISPR/Cas system for biometric recognition of targets and use biosensor strategy to read out biological signals without the employment of professional operations. Consequently, the CRISPR-based biosensors demonstrate great potential for the detection of biomarkers with high sensitivity and specificity. However, the signal readout still relies on specialized detectors, limiting its application in on-site detection for medical diagnosis. In this review, we summarize the principles and advances of the CRISPR-based biosensors with a focus on medical diagnosis. Then, we review the advantages and progress of CRISPR-based naked eye biosensors, which can realize diagnosis without additional detectors for signal readout. Finally, we discuss the challenges and further prospects for the development of CRISPR-based biosensors.

Surface Functionalized Titanium Nitride Electrode for CMOS Compatible Bioelectronic Devices

The development of bioelectronic devices is heading toward high throughput and high resolution. Yet, most electrode materials utilized in electrical biosensing are not compatible with the manufacturing techniques of semiconductor chips, which somehow hinders the integration and miniaturization of these devices. Titanium nitride (TiN) is a durable and economical material that is widely used in CMOS-based integrated circuits, bioelectronic systems, electrocatalytic systems, etc. Considering different application scenarios, new and efficient methods are required to functionalize TiN surface. In this study, a surface functionalization approach by covalent grafting of an organic thin film containing hydroxyl groups on TiN surface via electroreduction of diazonium salt 4-(2-hydroxyethyl)benzenediazonium was presented. Cyclic voltammetry (CV) procedures were carried out at the potential ranges of -0.8 V~0.5 V (vs Ag/AgCl) with varying numbers of potential cycles (i. e., 5, 25, and 50 cycles) in order to study the thickness of modification layer. Then, the electrochemical property, surface morphology, and chemical structures of the sample before and after modifications were investigated via multiple characterization techniques, such as CV, atomic force microscopy (AFM), scanning electron microscope (SEM) and X-ray photoelectron spectroscopy (XPS), etc., thereby confirming the successful grafting of hydroxyl groups onto the TiN surface. The experiments on DNA synthesis aimed to explore the potential of modified TiN electrode as a novel platform for DNA data storage applications and the corresponding proof-of-principle was accomplished by the process of coupling Cy3-phosphoramidite. Finally, the experiments were successfully reproduced on the randomly selected sites of the modified TiN microarray chips demonstrating the potential of technical protocol to extend applications in future bioelectronic devices, such as bio-sensing, high-throughput DNA synthesis, and molecular manipulation.

DNA functionalized programmable hybrid biomaterials for targeted multiplexed applications

With the advent of DNA nanotechnology, DNA-based biomaterials have emerged as a unique class of materials at the center of various biological advances. Owing to DNA's high modification capacity via programmable Watson-Crick base-pairing, DNA structures of desired design with increased complexity have been developed. However, the limited scalability, along with poor mechanical properties, high synthesis costs, and poor stability, reduced the adaptability of DNA-based materials to complex biological applications. DNA-based hybrid biomaterials were designed to overcome these limitations by conjugating DNA with functional materials. Today, DNA-based hybrid materials have attracted significant attention in biological engineering with broad application prospects in biomedicine, clinical diagnosis, and nanodevices. Here, we summarize the recent advances in DNA-based hybrid materials with an in-depth understanding of general molecular design principles, functionalities, and applications. Finally, the challenges and prospects associated with DNA-based hybrid materials are discussed at the end of this review.

Strategy, Design, and Fabrication of Electrochemical Biosensors: A Tutorial

Advanced healthcare requires novel technologies capable of real-time sensing to monitor acute and long-term health. The challenge relies on converting a real-time quantitative biological and chemical signal into a desired measurable output. Given the success in detecting glucose and the commercialization of glucometers, electrochemical biosensors continue to be a mainstay of academic and industrial research activities. Despite the wealth of literature on electrochemical biosensors, reports are often specific to a particular application (e.g., pathogens, cancer markers, glucose, etc.), and most fail to convey the underlying strategy and design, and if it is transferable to detection of a different analyte. Here we present a tutorial review for those entering this research area that summarizes the basic electrochemical techniques utilized as well as discusses the designs and optimization strategies employed to improve sensitivity and maximize signal output.

N. M, Choi W, Pan S. ResNet1D-Based Personal Identification with Multi-Session Surface Electromyography for Electronic Health Record Integration

Personal identification is an important aspect of managing electronic health records (EHRs), ensuring secure access to patient information, and maintaining patient privacy. Traditionally, biometric, signature, username/password, photo identity, etc., are employed for user authentication. However, these methods can be prone to security breaches, identity theft, and user inconvenience. The security of personal information is of paramount importance, particularly in the context of EHR. To address this, our study leverages ResNet1D, a deep learning architecture, to analyze surface electromyography (sEMG) signals for robust identification purposes. The proposed ResNet1D-based personal identification approach using the sEMG signal can offer an alternative and potentially more secure method for personal identification in EHR systems. We collected a multi-session sEMG signal database from individuals, focusing on hand gestures. The ResNet1D model was trained using this database to learn discriminative features for both gesture and personal identification tasks. For personal identification, the model validated an individual's identity by comparing captured features with their own stored templates in the healthcare EHR system, allowing secure access to sensitive medical information. Data were obtained in two channels when each of the 200 subjects performed 12 motions. There were three sessions, and each motion was repeated 10 times with time intervals of a day or longer between each session. Experiments were conducted on a dataset of 20 randomly sampled subjects out of 200 subjects in the database, achieving exceptional identification accuracy. The experiment was conducted separately for 5, 10, 15, and 20 subjects using the ResNet1D model of a deep neural network, achieving accuracy rates of 97%, 96%, 87%, and 82%, respectively. The proposed model can be integrated with healthcare EHR systems to enable secure and reliable personal identification and the safeguarding of patient information.

Dumbbell Dual-Hairpin Triggered DNA Nanonet Assembly for Cascade-Amplified Sensing of Exosomal MicroRNA

Exosomal microRNAs (miRNAs) are valuable biomarkers closely associated with cancer progression. Therefore, sensitive and specific exosomal miRNA biosensing has been employed for cancer diagnosis, prognosis, and prediction. In this study, a miRNA-based DNA nanonet assembly strategy is proposed, enabling the biosensing of exosomal miRNAs through dumbbell dual-hairpin under isothermal enzyme-free conditions. This strategy dexterously designs a specific dumbbell dual-hairpin that can selectively recognize exosomal miRNA, inducing conformational changes to cascade-generated X-shaped DNA structures, facilitating the extension of the X-shaped DNA in three-dimensional space, ultimately forming a DNA nanonet assembly. On the basis of the target miRNA, our design enriches the fluorescence signal through the cascade assembly of DNA nanonet and realizes the secondary signal amplification. Using exosomal miR-141 as the target, the resultant fluorescence sensing demonstrates an impressive detection limit of 57.6 pM and could identify miRNA sequences with single-base variants with high specificity. Through the analysis of plasma and urine samples, this method effectively distinguishes between benign prostatic hyperplasia, prostate cancer, and metastatic prostate cancer. Serving as a novel noninvasive and accurate screening and diagnostic tool for prostate cancer, this dumbbell dual-hairpin triggered DNA nanonet assembly strategy is promising for clinical applications.

A novel activation function based on DNA enzyme-free hybridization reaction and its implementation on nonlinear molecular learning systems

With the advent of the post-Moore's Law era, the development of traditional silicon-based computers has reached its limit, and there is an urgent need to develop new computing technologies to meet the needs of science, technology, and daily life. Due to its super-strong parallel computing capability and outstanding data storage capacity, DNA computing has become an important branch and hot research topic of new computer technology. DNA enzyme-free hybridization reaction technology is widely used in DNA computing, showing excellent performance in computing power and information processing. Studies have shown that DNA molecules not only have the computing function of electronic devices, but also exhibit certain human brain-like functions. In the field of artificial intelligence, activation functions play an important role as they enable artificial intelligence systems to fit and predict non-linear and complex variable relationships. Due to the difficulty of implementing activation functions in DNA computing, DNA circuits cannot easily achieve all the functions of artificial intelligence. DNA circuits need to rely on electronic computers to complete the training and learning process. Based on the parallel computing characteristics of DNA computing and the kinetic features of DNA molecule displacement reactions, this paper proposes a new activation function. This activation function can not only be easily implemented by DNA enzyme-free hybridization reaction reactions, but also has good nesting properties in DNA circuits, and can be cascaded with other DNA reactions to form a complete DNA circuit. This paper not only provides the mathematical analysis of the proposed activation function, but also provides a detailed analysis of its kinetic features. The activation function is then nested into a nonlinear neural network for DNA computing. This system is capable of fitting and predicting a certain nonlinear function.

Peptide-Based Flavivirus Biosensors: From Cell Structure to Virological and Serological Detection Methods

In tropical and developing countries, mosquito-borne diseases by flaviviruses pose a serious threat to public health. Early detection is critical for preventing their spread, but conventional methods are time-consuming and require skilled technicians. Biosensors have been developed to address this issue, but cross-reactivity with other flaviviruses remains a challenge. Peptides are essentially biomaterials used in diagnostics that allow virological and serological techniques to identify flavivirus selectively. This biomaterial originated as a small protein consisting of two to 50 amino acid chains. They offer flexibility in chemical modification and can be easily synthesized and applied to living cells in the engineering process. Peptides could potentially be developed as robust, low-cost, sensitive, and selective receptors for detecting flaviviruses. However, modification and selection of the receptor agents are crucial to determine the effectiveness of binding between the targets and the receptors. This paper addresses two potential peptide nucleic acids (PNAs) and affinity peptides that can detect flavivirus from another target-based biosensor as well as the potential peptide behaviors of flaviviruses. The PNAs detect flaviviruses based on the nucleotide base sequence of the target's virological profile via Watson-Crick base pairing, while the affinity peptides sense the epitope or immunological profile of the targets. Recent developments in the functionalization of peptides for flavivirus biosensors are explored in this Review by division into electrochemical, optical, and other detection methods.

Improving DNA nanostructure stability: A review of the biomedical applications and approaches

DNA's programmable, predictable, and precise self-assembly properties enable structural DNA nanotechnology. DNA nanostructures have a wide range of applications in drug delivery, bioimaging, biosensing, and theranostics. However, physiological conditions, including low cationic ions and the presence of nucleases in biological systems, can limit the efficacy of DNA nanostructures. Several strategies for stabilizing DNA nanostructures have been developed, including i) coating them with biomolecules or polymers, ii) chemical cross-linking of the DNA strands, and iii) modifications of the nucleotides and nucleic acids backbone. These methods significantly enhance the structural stability of DNA nanostructures and thus enable in vivo and in vitro applications. This study reviews the present perspective on the distinctive properties of the DNA molecule and explains various DNA nanostructures, their advantages, and their disadvantages. We provide a brief overview of the biomedical applications of DNA nanostructures and comprehensively discuss possible approaches to improve their biostability. Finally, the shortcomings and challenges of the current biostability approaches are examined.

DNA and Nanomaterials: A Functional Combination for DNA Sensing

Recent decades have experienced tough situations due to the lack of reliable diagnostic facilities. The most recent cases occurred during the pandemic, where researchers observed the lack of diagnostic facilities with precision. Microorganisms and viral disease's ability to escape diagnosis has been a global challenge. DNA always has been a unique moiety with a strong and precise base-paired structure. DNA in human and foreign particles makes identification possible through base pairing. Since then, researchers have focused heavily on designing diagnostic assays targeting DNA in particular. Moreover, DNA nanotechnology has contributed vastly to designing composite nanomaterials by combining DNA/nucleic acids with functional nanomaterials and inorganic nanoparticles exploiting their physicochemical properties. These nanomaterials often exhibit unique or enhanced properties due to the synergistic activity of the many components. The capabilities of DNA and additional nanomaterials have shown the combination of robust and advanced tailoring of biosensors. Preceding findings state that the conventional strategies have exhibited certain limitations such as a low range of target detection, less biodegradability, subordinate half-life, and high susceptibility to microenvironments; however, a DNA-nanomaterial-based biosensor has overcome these limitations meaningfully. Additionally, the unique properties of nucleic acids have been studied extensively due to their high signal conduction abilities. Here, we review recent studies on DNA-nanomaterial-based biosensors, their mechanism of action, and improved/updated strategies in vivo and in situ. Furthermore, this review highlights the recent methodologies on DNA utilization to exploit the interfacial properties of nanomaterials in DNA sensing. Lastly, the review concludes with the limitations/challenges and future directions.

Label-Free Biochemical Sensing Using Processed Optical Fiber Interferometry: A Review

Over the last 20 years, optical fiber-based devices have been exploited extensively in the field of biochemical sensing, with applications in many specific areas such as the food processing industry, environmental monitoring, health diagnosis, bioengineering, disease diagnosis, and the drug industry due to their compact, label-free, and highly sensitive detection. The selective and accurate detection of biochemicals is an essential part of biosensing devices, which is to be done through effective functionalization of highly specific recognition agents, such as enzymes, DNA, receptors, etc., over the transducing surface. Among many optical fiber-based sensing technologies, optical fiber interferometry-based biosensors are one of the broadly used methods with the advantages of biocompatibility, compact size, high sensitivity, high-resolution sensing, lower detection limits, operating wavelength tunability, etc. This Review provides a comprehensive review of the fundamentals as well as the current advances in developing optical fiber interferometry-based biochemical sensors. In the beginning, a generic biosensor and its several components are introduced, followed by the fundamentals and state-of-art technology behind developing a variety of interferometry-based fiber optic sensors. These include the Mach-Zehnder interferometer, the Michelson interferometer, the Fabry-Perot interferometer, the Sagnac interferometer, and biolayer interferometry (BLI). Further, several technical reports are comprehensively reviewed and compared in a tabulated form for better comparison along with their advantages and disadvantages. Further, the limitations and possible solutions for these sensors are discussed to transform these in-lab devices into commercial industry applications. At the end, in conclusion, comments on the prospects of field development toward the commercialization of sensor technology are also provided. The Review targets a broad range of audiences including beginners and also motivates the experts helping to solve the real issues for developing an industry-oriented sensing device.

Electroanalysis in Pharmacogenomic Studies: Mechanisms of Drug Interaction with DNA

The review discusses electrochemical methods for analysis of drug interactions with DNA. The electroanalysis method is based on the registration of interaction-induced changes in the electrochemical oxidation potential of heterocyclic nitrogenous bases in the DNA molecule and in the maximum oxidation current amplitude. The mechanisms of DNA-drug interactions can be identified based on the shift in the electrooxidation potential of heterocyclic nitrogenous bases toward more negative (cathodic) or positive (anodic) values. Drug intercalation into DNA shifts the electrochemical oxidation potential to positive values, indicating thermodynamically unfavorable process that hinders oxidation of nitrogenous bases in DNA. The potential shift toward the negative values indicates electrostatic interactions, e.g., drug binding in the DNA minor groove, since this process does not interfere with the electrochemical oxidation of bases. The concentration-dependent decrease in the intensity of electrochemical oxidation of DNA bases allows to quantify the type of interaction and calculate the binding constants.

NICE-FF: A non-empirical, intermolecular, consistent, and extensible force field for nucleic acids and beyond

A new non-empirical ab initio intermolecular force field (NICE-FF in buffered 14-7 potential form) has been developed for nucleic acids and beyond based on the dimer interaction energies (IEs) calculated at the spin component scaled-MI-second order Møller-Plesset perturbation theory. A fully automatic framework has been implemented for this purpose, capable of generating well-polished computational grids, performing the necessary ab initio calculations, conducting machine learning (ML) assisted force field (FF) parametrization, and extending existing FF parameters by incorporating new atom types. For the ML-assisted parametrization of NICE-FF, interaction energies of ∼18 000 dimer geometries (with IE < 0) were used, and the best fit gave a mean square deviation of about 0.46 kcal/mol. During this parametrization, atom types apparent in four deoxyribonucleic acid (DNA) bases have been first trained using the generated DNA base datasets. Both uracil and hypoxanthine, which contain the same atom types found in DNA bases, have been considered as test molecules. Three new atom types have been added to the DNA atom types by using IE datasets of both pyrazinamide and 9-methylhypoxanthine. Finally, the last test molecule, theophylline, has been selected, which contains already-fitted atom-type parameters. The performance of NICE-FF has been investigated on the S22 dataset, and it has been found that NICE-FF outperforms the well-known FFs by generating the most consistent IEs with the high-level ab initio ones. Moreover, NICE-FF has been integrated into our in-house developed crystal structure prediction (CSP) tool [called FFCASP (Fast and Flexible CrystAl Structure Predictor)], aiming to find the experimental crystal structures of all considered molecules. CSPs, which were performed up to 4 formula units (Z), resulted in NICE-FF being able to locate almost all the known experimental crystal structures with sufficiently low RMSD20 values to provide good starting points for density functional theory optimizations.

Structure and stability of different triplets involving artificial nucleobases: clues for the formation of semisynthetic triple helical DNA

A triple helical DNA can control gene expression, help in homologous recombination, induce mutations to facilitate DNA repair mechanisms, suppress oncogene formations, etc. However, the structure and function of semisynthetic triple helical DNA are not known. To understand this, various triplets formed between eight artificial nucleobases (P, Z, J, V, B, S, X, and K) and four natural DNA bases (G, C, A, and T) are studied herein by employing a reliable density functional theoretic (DFT) method. Initially, the triple helix-forming artificial nucleobases interacted with the duplex DNA containing GC and AT base pairs, and subsequently, triple helix-forming natural bases (G and C) interacted with artificial duplex DNA containing PZ, JV, BS, and XK base pairs. Among the different triplets formed in the first category, the C-JV triplet is found to be the most stable with a binding energy of about - 31 kcal/mol. Similarly, among the second category of triplets, the Z-GC and V-GC triplets are the most stable. Interestingly, Z-GC and V-GC are found to be isoenergetic with a binding energy of about - 30 kcal/mol. The C-JV, and Z-GC or V-GC triplets are about 12-14 kcal/mol more stable than the JV and GC base pairs respectively. Microsolvation of these triplets in 5 explicit water molecules further enhanced their stability by 16-21 kcal/mol. These results along with the consecutive stacking of the C-JV triplet (C-JV/C-JV) data indicate that the synthetic nucleobases can form stable semisynthetic triple helical DNA. However, consideration of a full-length DNA containing one or more semisynthetic bases or base pairs is necessary to understand the formation of semisynthetic DNA in living cells.

Recent and Advanced DNA-Based Technologies for the Authentication of Probiotic, Protected Designation of Origin (PDO) and Protected Geographical Indication (PGI) Fermented Foods and Beverages

The authenticity of probiotic products and fermented foods and beverages that have the status of protected designation of origin (PDO) or geographical indication (PGI) can be assessed via numerous methods. DNA-based technologies have emerged in recent decades as valuable tools to achieve food authentication, and advanced DNA-based methods and platforms are being developed. The present review focuses on the recent and advanced DNA-based techniques for the authentication of probiotic, PDO and PGI fermented foods and beverages. Moreover, the most promising DNA-based detection tools are presented. Strain- and species-specific DNA-based markers of microorganisms used as starter cultures or (probiotic) adjuncts for the production of probiotic and fermented food and beverages have been exploited for valuable authentication in several detection methods. Among the available technologies, propidium monoazide (PMA) real-time polymerase chain reaction (PCR)-based technologies allow for the on-time quantitative detection of viable microbes. DNA-based lab-on-a-chips are promising devices that can be used for the on-site and on-time quantitative detection of microorganisms. PCR-DGGE and metagenomics, even combined with the use of PMA, are valuable tools allowing for the fingerprinting of the microbial communities, which characterize PDO and PGI fermented foods and beverages, and they are necessary for authentication besides permitting the detection of extra or mislabeled species in probiotic products. These methods, in relation to the authentication of probiotic foods and beverages, need to be used in combination with PMA, culturomics or flow cytometry to allow for the enumeration of viable microorganisms.

Emerging Applications of Nanobiosensors in Pathogen Detection in Water and Food

Food and waterborne illnesses are still a major concern in health and food safety areas. Every year, almost 0.42 million and 2.2 million deaths related to food and waterborne illness are reported worldwide, respectively. In foodborne pathogens, bacteria such as Salmonella, Shiga-toxin producer Escherichia coli, Campylobacter, and Listeria monocytogenes are considered to be high-concern pathogens. High-concern waterborne pathogens are Vibrio cholerae, leptospirosis, Schistosoma mansoni, and Schistosima japonicum, among others. Despite the major efforts of food and water quality control to monitor the presence of these pathogens of concern in these kinds of sources, foodborne and waterborne illness occurrence is still high globally. For these reasons, the development of novel and faster pathogen-detection methods applicable to real-time surveillance strategies are required. Methods based on biosensor devices have emerged as novel tools for faster detection of food and water pathogens, in contrast to traditional methods that are usually time-consuming and are unsuitable for large-scale monitoring. Biosensor devices can be summarized as devices that use biochemical reactions with a biorecognition section (isolated enzymes, antibodies, tissues, genetic materials, or aptamers) to detect pathogens. In most cases, biosensors are based on the correlation of electrical, thermal, or optical signals in the presence of pathogen biomarkers. The application of nano and molecular technologies allows the identification of pathogens in a faster and high-sensibility manner, at extremely low-pathogen concentrations. In fact, the integration of gold, silver, iron, and magnetic nanoparticles (NP) in biosensors has demonstrated an improvement in their detection functionality. The present review summarizes the principal application of nanomaterials and biosensor-based devices for the detection of pathogens in food and water samples. Additionally, it highlights the improvement of biosensor devices through nanomaterials. Nanomaterials offer unique advantages for pathogen detection. The nanoscale and high specific surface area allows for more effective interaction with pathogenic agents, enhancing the sensitivity and selectivity of the biosensors. Finally, biosensors' capability to functionalize with specific molecules such as antibodies or nucleic acids facilitates the specific detection of the target pathogens.

The synthesis and functionalization of metal organic frameworks and their applications for the selective separation of proteins/peptides

Recently, proteins separation has drawn great interest for the full investigation of a proteome because the proteins separation is the precondition when conducting clinical research or proteomics research. Metal organic frameworks (MOFs) are fabricated via covalent connection between organic ligands and metal ions/clusters units. MOFs have attracted much attention due to the ultra-high specific surface area, tunable structure, more metal site or unsaturated site, and chemical stability. Over the past decade, different functionalization types of MOFs have been reported in combination with amino acids, nucleic acids, proteins, polymers, and nanoparticles for various applications. In this review, the synthesis and functionalization of MOFs have been thoroughly discussed, and we introduced the existing problems and development trends in these fields. Furthermore, MOFs as advanced adsorbents for selective separation of proteins/peptides are summarized. Additionally, we present a comprehensive prospects and challenges in the preparation of robust functional MOFs-based adsorbents and make a final outlook on their future development prospects in selective separation of proteins/peptides.

Paper-Based Aptasensors: Working Principles, Detection Modes, and Applications

Aptamers are short oligonucleotides designed to possess high binding affinity towards specific target compounds (ions, molecules, or cells). Due to their function and unique advantages, aptamers are considered viable alternatives to antibodies as biorecognition elements in bioassays and biosensors. On the other hand, paper-based devices (PADs) have emerged as a promising and powerful technology for the fabrication of low-cost analytical tools, mainly intended for on-site and point-of-care applications. The present work aims to provide a comprehensive overview of paper-based aptasensors. The review describes the fabrication methods and working principles of paper-based devices, the properties of aptamers as bioreceptors, the different modes of detection used in conjunction with aptasensing PADs, and representative applications for the detection of ions, small molecules, proteins, and cells. The future challenges and prospects of these devices are also discussed.

Recent Advances in DNA Nanotechnology-Enabled Biosensors for Virus Detection

Virus-related infectious diseases are serious threats to humans, which makes virus detection of great importance. Traditional virus-detection methods usually suffer from low sensitivity and specificity, are time-consuming, have a high cost, etc. Recently, DNA biosensors based on DNA nanotechnology have shown great potential in virus detection. DNA nanotechnology, specifically DNA tiles and DNA aptamers, has achieved atomic precision in nanostructure construction. Exploiting the programmable nature of DNA nanostructures, researchers have developed DNA nanobiosensors that outperform traditional virus-detection methods. This paper reviews the history of DNA tiles and DNA aptamers, and it briefly describes the Baltimore classification of virology. Moreover, the advance of virus detection by using DNA nanobiosensors is discussed in detail and compared with traditional virus-detection methods. Finally, challenges faced by DNA nanobiosensors in virus detection are summarized, and a perspective on the future development of DNA nanobiosensors in virus detection is also provided.

Nanomaterial interfaces designed with different biorecognition elements for biosensing of key foodborne pathogens

Foodborne diseases caused by pathogen bacteria are a serious problem toward the safety of human life in a worldwide. Conventional methods for pathogen bacteria detection have several handicaps, including trained personnel requirement, low sensitivity, laborious enrichment steps, low selectivity, and long-term experiments. There is a need for precise and rapid identification and detection of foodborne pathogens. Biosensors are a remarkable alternative for the detection of foodborne bacteria compared to conventional methods. In recent years, there are different strategies for the designing of specific and sensitive biosensors. Researchers activated to develop enhanced biosensors with different transducer and recognition elements. Thus, the aim of this study was to provide a topical and detailed review on aptamer, nanofiber, and metal organic framework-based biosensors for the detection of food pathogens. First, the conventional methods, type of biosensors, common transducer, and recognition element were systematically explained. Then, novel signal amplification materials and nanomaterials were introduced. Last, current shortcomings were emphasized, and future alternatives were discussed.

Light-Up Split Broccoli Aptamer as a Versatile Tool for RNA Assembly Monitoring in Cell-Free TX-TL Systems, Hybrid RNA/DNA Origami Tagging and DNA Biosensing

Binary light-up aptamers are intriguing and emerging tools with potential in different fields. Herein, we demonstrate the versatility of a split Broccoli aptamer system able to turn on the fluorescence signal only in the presence of a complementary sequence. First, an RNA three-way junction harbouring the split system is assembled in an E. coli-based cell-free TX-TL system where the folding of the functional aptamer is demonstrated. Then, the same strategy is introduced into a 'bio-orthogonal' hybrid RNA/DNA rectangle origami characterized by atomic force microscopy: the activation of the split system through the origami self-assembly is demonstrated. Finally, our system is successfully used to detect the femtomoles of a Campylobacter spp. DNA target sequence. Potential applications of our system include the real-time monitoring of the self-assembly of nucleic-acid-based devices in vivo and of the intracellular delivery of therapeutic nanostructures, as well as the in vitro and in vivo detection of different DNA/RNA targets.

A survey on molecular-scale learning systems with relevance to DNA computing

DNA computing has emerged as a promising alternative to achieve programmable behaviors in chemistry by repurposing the nucleic acid molecules into chemical hardware upon which synthetic chemical programs can be executed. These chemical programs are capable of simulating diverse behaviors, including boolean logic computation, oscillations, and nanorobotics. Chemical environments such as the cell are marked by uncertainty and are prone to random fluctuations. For this reason, potential DNA-based molecular devices that aim to be deployed into such environments should be capable of adapting to the stochasticity inherent in them. In keeping with this goal, a new subfield has emerged within DNA computing, focusing on developing approaches that embed learning and inference into chemical reaction systems. If realized in biochemical contexts, such molecular machines can engender novel applications in fields such as biotechnology, synthetic biology, and medicine. Therefore, it would be beneficial to review how different ideas were conceived, how the progress has been so far, and what the emerging ideas are in this nascent field of 'molecular-scale learning'.

A DNA biosensors-based microfluidic platform for attomolar real-time detection of unamplified SARS-CoV-2 virus

The emergence of the coronavirus 2019 (COVID-19) arose the need for rapid, accurate and massive virus detection methods to control the spread of infectious diseases. In this work, a device, deployable in non-medical environments, has been developed for the detection of non-amplified SARS-CoV-2 RNA. A SARS-CoV-2 specific probe was designed and covalently immobilized at the surface of glass slides to fabricate a DNA biosensor. The resulting system was integrated in a microfluidic platform, in which viral RNA was extracted from non-treated human saliva, before hybridizing at the surface of the sensor. The formed DNA/RNA duplex was detected in presence of SYBR Green I using an opto-electronic system, based on a high-power LED and a photo multiplier tube, which convert the emitted fluorescence into an electrical signal that can be processed in less than 10 min. The limit of detection of the resulting microfluidic platform reached six copies of viral RNA per microliter of sample (equal to 10 aM) and satisfied the safety margin. The absence of non-specific adsorption and the selectivity for SARS-CoV-2 RNA were established. In addition, the designed device could be applicable for the detection of a variety of viruses by simple modification of the immobilized probe.

Machine learning for detecting DNA attachment on SPR biosensor

Optoelectric biosensors measure the conformational changes of biomolecules and their molecular interactions, allowing researchers to use them in different biomedical diagnostics and analysis activities. Among different biosensors, surface plasmon resonance (SPR)-based biosensors utilize label-free and gold-based plasmonic principles with high precision and accuracy, allowing these gold-based biosensors as one of the preferred methods. The dataset generated from these biosensors are being used in different machine learning (ML) models for disease diagnosis and prognosis, but there is a scarcity of models to develop or assess the accuracy of SPR-based biosensors and ensure a reliable dataset for downstream model development. Current study proposed innovative ML-based DNA detection and classification models from the reflective light angles on different gold surfaces of biosensors and associated properties. We have conducted several statistical analyses and different visualization techniques to evaluate the SPR-based dataset and applied t-SNE feature extraction and min-max normalization to differentiate classifiers of low-variances. We experimented with several ML classifiers, namely support vector machine (SVM), decision tree (DT), multi-layer perceptron (MLP), k-nearest neighbors (KNN), logistic regression (LR) and random forest (RF) and evaluated our findings in terms of different evaluation metrics. Our analysis showed the best accuracy of 0.94 by RF, DT and KNN for DNA classification and 0.96 by RF and KNN for DNA detection tasks. Considering area under the receiver operating characteristic curve (AUC) (0.97), precision (0.96) and F1-score (0.97), we found RF performed best for both tasks. Our research shows the potentiality of ML models in the field of biosensor development, which can be expanded to develop novel disease diagnosis and prognosis tools in the future.

Aptamer against Aflatoxin B1 Obtained by SELEX and Applied in Detection

Aflatoxins, especially aflatoxin B1 (AFB1), are the most prevalent mycotoxins in nature. They contaminate various crops and cause global food and feed safety concerns. Therefore, a simple, rapid, sensitive, and specific AFB1 detection tool is urgently needed. Aptamers generated by SELEX technology can specifically bind the desired targets with high affinity. The broad range of targets expands the scope of applications for aptamers. We used an AFB1-immobilized magnetic nanoparticle for SELEX to select AFB1-specific aptamers. One aptamer, fl-2CS1, revealed a dissociation constant (Kd = 2.5 μM) with AFB1 determined by isothermal titration calorimetry. Furthermore, no interaction was shown with other toxins (AFB2, AFG1, AFG2, OTA, and FB1). According to structural prediction and analysis, we identified a short version of the AFB1-specific aptamer, fl-2CS1/core, with a minimum length of 39-mer used in the AFB1-aptasensor system by real-time qPCR. The aptasensor showed a broad range of detection from 50 ppt to 50 ppb with an accuracy of 90% in the spiked peanut extract samples. With the application of the AFB1-aptasensor we have constructed, a wide range detection tool with high accuracy might be developed as a point-of-care testing tool in agriculture.

Preparation, applications, and challenges of functional DNA nanomaterials

As a carrier of genetic information, DNA is a versatile module for fabricating nanostructures and nanodevices. Functional molecules could be integrated into DNA by precise base complementary pairing, greatly expanding the functions of DNA nanomaterials. These functions endow DNA nanomaterials with great potential in the application of biomedical field. In recent years, functional DNA nanomaterials have been rapidly investigated and perfected. There have been reviews that classified DNA nanomaterials from the perspective of functions, while this review primarily focuses on the preparation methods of functional DNA nanomaterials. This review comprehensively introduces the preparation methods of DNA nanomaterials with functions such as molecular recognition, nanozyme catalysis, drug delivery, and biomedical material templates. Then, the latest application progress of functional DNA nanomaterials is systematically reviewed. Finally, current challenges and future prospects for functional DNA nanomaterials are discussed.