Aptamer-based plasmonic sensor array for discrimination of proteins and cells with the naked eye

Colorimetric sensing for translational applications: from colorants to mechanisms

Colorimetric sensing offers instant reporting via visible signals. Versus labor-intensive and instrument-dependent detection methods, colorimetric sensors present advantages including short acquisition time, high throughput screening, low cost, portability, and a user-friendly approach. These advantages have driven substantial growth in colorimetric sensors, particularly in point-of-care (POC) diagnostics. Rapid progress in nanotechnology, materials science, microfluidics technology, biomarker discovery, digital technology, and signal pattern analysis has led to a variety of colorimetric reagents and detection mechanisms, which are fundamental to advance colorimetric sensing applications. This review first summarizes the basic components (e.g., color reagents, recognition interactions, and sampling procedures) in the design of a colorimetric sensing system. It then presents the rationale design and typical examples of POC devices, e.g., lateral flow devices, microfluidic paper-based analytical devices, and wearable sensing devices. Two highlighted colorimetric formats are discussed: combinational and activatable systems based on the sensor-array and lock-and-key mechanisms, respectively. Case discussions in colorimetric assays are organized by the analyte identities. Finally, the review presents challenges and perspectives for the design and development of colorimetric detection schemes as well as applications. The goal of this review is to provide a foundational resource for developing colorimetric systems and underscoring the colorants and mechanisms that facilitate the continuing evolution of POC sensors.

Surface-Engineered Nanomaterials for Optical Array Based Sensing

Array based sensing governed by optical methods provides fast and economic way for detection of wide variety of analytes where the ideality of detection processes depends on the sensor element's versatile mode of interaction with multiple analytes in an unbiased manner. This can be achieved by either the receptor unit having multiple recognition moiety, or their surface property should possess tuning ability upon fabrication called surface engineering. Nanomaterials have a high surface to volume ratio, making them viable candidates for molecule recognition through surface adsorption phenomena, which makes it ideal to meet the above requirements. Most crucially, by engineering a nanomaterial's surface, one may produce cross-reactive responses for a variety of analytes while focusing solely on a single nanomaterial. Depending on the nature of receptor elements, in the last decade the array-based sensing has been considering as multimodal detection platform which operates through various pathway including single channel, multichannel, binding and indicator displacement assay, sequential ON-OFF sensing, enzyme amplified and nanozyme based sensing etc. In this review we will deliver the working principle for Array-based sensing by using various nanomaterials like nanoparticles, nanosheets, nanodots and self-assembled nanomaterials and their surface functionality for suitable molecular recognition.

Development of Optical Differential Sensing Based on Nanomaterials for Biological Analysis

The discrimination and recognition of biological targets, such as proteins, cells, and bacteria, are of utmost importance in various fields of biological research and production. These include areas like biological medicine, clinical diagnosis, and microbiology analysis. In order to efficiently and cost-effectively identify a specific target from a wide range of possibilities, researchers have developed a technique called differential sensing. Unlike traditional "lock-and-key" sensors that rely on specific interactions between receptors and analytes, differential sensing makes use of cross-reactive receptors. These sensors offer less specificity but can cross-react with a wide range of analytes to produce a large amount of data. Many pattern recognition strategies have been developed and have shown promising results in identifying complex analytes. To create advanced sensor arrays for higher analysis efficiency and larger recognizing range, various nanomaterials have been utilized as sensing probes. These nanomaterials possess distinct molecular affinities, optical/electrical properties, and biological compatibility, and are conveniently functionalized. In this review, our focus is on recently reported optical sensor arrays that utilize nanomaterials to discriminate bioanalytes, including proteins, cells, and bacteria.

Identification of Proteins Using Supramolecular Gold Nanoparticle-Dye Sensor Arrays

The rapid detection of proteins is very important in the early diagnosis of diseases. Gold nanoparticles (AuNPs) can be engineered to bind biomolecules efficiently and differentially. Cross-reactive sensor arrays have high sensitivity for sensing proteins using differential interactions between sensor elements and bioanalytes. A new sensor array was fabricated using surface-charged AuNPs with dyes supramolecularly encapsulated into the AuNP monolayer. The fluorescence of dyes is partially quenched by the AuNPs and can be restored or further quenched due to the differential interactions between AuNPs with proteins. This sensing system enables the discrimination of proteins in both buffer and human serum, providing a potential tool for real-world disease diagnostics.

Carbocyanine-Based Optical Sensor Array for the Discrimination of Proteins and Rennet Samples Using Hypochlorite Oxidation

Optical sensor arrays are widely used in obtaining fingerprints of samples, allowing for solutions of recognition and identification problems. An approach to extending the functionality of the sensor arrays is using a kinetic factor by conducting indicator reactions that proceed at measurable rates. In this study, we propose a method for the discrimination of proteins based on their oxidation by sodium hypochlorite with the formation of the products, which, in turn, feature oxidation properties. As reducing agents to visualize these products, carbocyanine dyes IR-783 and Cy5.5-COOH are added to the reaction mixture at pH 5.3, and different spectral characteristics are registered every several minutes (absorbance in the visible region and fluorescence under excitation by UV (254 and 365 nm) and red light). The intensities of the photographic images of the 96-well plate are processed by principal component analysis (PCA) and linear discriminant analysis (LDA). Six model proteins (bovine and human serum albumins, γ-globulin, lysozyme, pepsin, and proteinase K) and 10 rennet samples (mixtures of chymosin and pepsin from different manufacturers) are recognized by the proposed method. The method is rapid and simple and uses only commercially available reagents.

Recent progress of aptamer‒drug conjugates in cancer therapy

Aptamers are single-stranded DNA or RNA sequences that can specifically bind with the target protein or molecule via specific secondary structures. Compared to antibody-drug conjugates (ADC), aptamer‒drug conjugate (ApDC) is also an efficient, targeted drug for cancer therapy with a smaller size, higher chemical stability, lower immunogenicity, faster tissue penetration, and facile engineering. Despite all these advantages, several key factors have delayed the clinical translation of ApDC, such as in vivo off-target effects and potential safety issues. In this review, we highlight the most recent progress in the development of ApDC and discuss solutions to the problems noted above.

Colorimetric Sensor Array for Identification of Proteins and Classification of Metabolic Profiles under Various Osmolyte Conditions

Rapid and efficient detection and identification of proteins hold great promise in medical diagnostics, treatment of different diseases, and proteomics. Here, we present a simple colorimetric sensor array for the differentiation of proteins in various osmolyte solutions. Osmolytes have different influences on the conformation of proteins, which have differential binding to silver nanoparticles, resulting in color changes. The sensor array shows unique color change patterns for each of the 19 proteins, allowing unambiguous identification. Very interestingly, the differentiation of 19 proteins is related to their molecular weight. Moreover, the sensor array can be used to identify protein mixtures, thermal denaturized proteins, and unknown protein samples. Finally, the sensor array can also analyze the plasma or liver samples of the four groups of salt-sensitive rats fed with different diets, indicating that it has the potential for the classification of metabolic profiles.

Mixed-Ligand gold nanoparticles based optical sensor array for the recognition and quantification of seven toxic metals

Sensor arrays use pattern recognition for the identification and quantification of analytes. In the presented work, a gold nanoparticle (GNP) based optical sensor array was employed to classify and quantify seven toxic metals (arsenic, barium, cadmium, cerium, chromium, lead, and mercury). The sensor array receptors were GNPs functionalized by mercaptoundecanoic acid, 2-mercaptoethanesulfonate, and a 1:1 mixture of the two ligands. The mixed-ligand particle responds to the same analytes as the mono-ligand particles but in a distinctive way. This behavior demonstrates the high potential of mixed-ligand particles in the fabrication of sensor array receptors. The responses of the GNPs to different concentrations of the seven metal ions were analyzed, and a unique "classification trajectory" was produced for every metal. Samples of different metal concentrations were then measured and identified using the "classification trajectories". Once sample composition has been identified, a PLSR model, produced from the concatenated sensor array spectra of four calibration samples for each nanoparticle, was used to determine the metal concentration.

Carbon Quantum Dots Based Chemosensor Array for Monitoring Multiple Metal Ions

The simultaneous identification of multiple metal ions in water has attracted enormous research interest in the past few decades. We herein describe a novel method for multiple metal ion detection using a carbon quantum dots (CQDs)-based chemosensor array and the CQDs are functionalized with different amino acids (glutamine, histidine, arginine, lysine and proline), which act as sensing elements in the sensor array. Eleven metal ions are successfully identified by the designed chemosensor array, with 100% classification accuracy. Importantly, the proposed method allowed the quantitative prediction of the concentration of individual metal ions in the mixture with the aid of a support vector machine (SVM). The sensor array also enables the qualitative detection of unknown metal ions under the interference of tap water and local river water. Thus, the strategy provides a novel high-throughput approach for the identification of various analytes in complex systems.

Recent Advances in Electrochemical Sensing of Hydrogen Peroxide (H2O2) Released from Cancer Cells

Cancer is by far the most common cause of death worldwide. There are more than 200 types of cancer known hitherto depending upon the origin and type. Early diagnosis of cancer provides better disease prognosis and the best chance for a cure. This fact prompts world-leading scientists and clinicians to develop techniques for the early detection of cancer. Thus, less morbidity and lower mortality rates are envisioned. The latest advancements in the diagnosis of cancer utilizing nanotechnology have manifested encouraging results. Cancerous cells are well known for their substantial amounts of hydrogen peroxide (H₂O₂). The common methods for the detection of H₂O₂ include colorimetry, titration, chromatography, spectrophotometry, fluorimetry, and chemiluminescence. These methods commonly lack selectivity, sensitivity, and reproducibility and have prolonged analytical time. New biosensors are reported to circumvent these obstacles. The production of detectable amounts of H₂O₂ by cancerous cells has promoted the use of bio- and electrochemical sensors because of their high sensitivity, selectivity, robustness, and miniaturized point-of-care cancer diagnostics. Thus, this review will emphasize the principles, analytical parameters, advantages, and disadvantages of the latest electrochemical biosensors in the detection of H₂O₂. It will provide a summary of the latest technological advancements of biosensors based on potentiometric, impedimetric, amperometric, and voltammetric H₂O₂ detection. Moreover, it will critically describe the classification of biosensors based on the material, nature, conjugation, and carbon-nanocomposite electrodes for rapid and effective detection of H₂O₂, which can be useful in the early detection of cancerous cells.

Aptamer/AuNPs encoders endow precise identification and discrimination of lipoprotein subclasses

Lipoproteins are composed of lipid and apolipoproteins in conjunction with noncovalent bonds. Different lipoprotein categories, particularly Low-Density Lipoprotein (LDL), High-Density Lipoprotein (HDL) and Very Low-Density Lipoprotein (VLDL) disagree in roles for the occurrence and development of cardiovascular disease, and their exact discrimination are critically required. Herein, a multiplexed sensor platform combined with an encoder system is introduced for accurate analysis of multiple lipoproteins in complex matrix. Three encoders, i.e., bare AuNPs, AuNPs-anti-LDL aptamer (AuNPs-apt) and AuNPs-non-aptamer DNA (AuNPs-n), facilitate precise discrimination for lipoprotein subclasses at a fairly low level of 0.490 nM. The binding of single-stranded DNA (ssDNA) with AuNPs prevents them from gathering in a relatively higher level of salt. In targets stimuli, the weaker binding between ssDNA and AuNPs is destroyed to certain degrees depending on the differential affinities among DNA, AuNPs, and multifarious proteins. It results in distinct aggregation states of encoders to cause diverse ultraviolet absorption, which may be statistically characterized to achieve highly facile and precise identification for lipoprotein subclasses. Remarkably, LDL at 0.05-37.5 μg/mL could be identified by the encoder system. 11 typical proteins including three lipoprotein subclasses in human serum were also precisely discriminated. Furthermore, the accurate identification of lipoprotein subclasses with different molar ratios from real clinical serum samples were obtained.

Particle-in-a-frame gold nanomaterials with an interior nanogap-based sensor array for versatile analyte detection

In this work, we studied the catalytic performance of gold nanomaterials, specifically a particle-in-a-frame nanostructure (PIAF) with interior nanogaps. Au PIAF was used to catalyse the 3,3',5,5'-tetramethylbenzidine (TMB) reaction. This array could accurately identify 7 proteins, 5 antioxidants, and 3 cell types.

Development of pattern recognition based on nanosheet-DNA probes and an extendable DNA library

Pattern recognition, also called "array sensing," is a recognition strategy with a wide and expandable analysis range, based on high-throughput analysis data. In this work, we constructed a sensor array for the identification of targets including bacterial pathogens and proteins by using FAM-labeled DNA probes and 2D nanosheet materials. We designed an ordered and extendible DNA library for the collection of recognition probes. Unlike traditional DNA probes with random and massive sequences, our DNA library was constructed following a 5-digit binary number (00000-11111, 0 = CCC, and 1 = TTT), and especially, 8 special symmetry sequences were chosen from the library. Two different nanosheet materials were used as the quencher. When targets were added, the interaction between DNA and the nanosheets was competitively affected, and as a result, the fluorescence signal changed accordingly. Finally, by using our fluorescent sensor array, 17 bacteria and 8 proteins were precisely recognized. We believe that our work has provided a simple and valuable strategy for the improvement of the recognition range and discrimination precision for the development of pattern recognition.

Discrimination of deletion to point cytokine mutants based on an array of cross-reactive receptors mimicking protein recognition by heparan sulfate

Differential sensing of proteins based on cross-reactive arrays and pattern recognition is a promising technique for the detection and identification of proteins. In this study, a rational biomimetic strategy has been used to prepare sensing materials capable of discriminating structurally similar proteins, such as deletion and point mutants of a cytokine, by mimicking the biological properties of heparan sulfate (HS). Using the self-assembly of two disaccharides, lactose and sulfated lactose at various ratios on the surface of a chip, an array of combinatorial cross-reactive receptors has been prepared. Coupling with surface plasmon resonance imaging (SPRi), the obtained cross-reactive array is very efficient for protein sensing. It is able to detect HS binding proteins (HSbps) such as IFNγ at nanomolar concentrations. Moreover, such a system is capable of discriminating between IFNγ and its mutants with good selectivity.

Inkjet-printed paper-based sensor array for highly accurate pH sensing

In this work, a novel paper-based colorimetric sensor array was developed by inkjet printing method with polyethylene glycol (PEG) immobilization system. Eight commercially available pH indicators with sequential pH segments in nearly whole pH range were dissolved in nine mixed inks to fabricate the 3 × 3 sensor array on mixed cellulose ester (MCE) paper. Based on homogeneous deposition of inkjet printing, the eight pH indicators were sufficiently immobilized on MCE paper with the assistance of PEG-400, which guaranteed pH detection of aqueous samples on sensor array without hydrophobic barriers. Besides, the indicating range of each indicator obtained an extension through the addition of PEG 400, which remarkably enriched the distinguishable capability of sensor array and benefited for high resolution of pH detection. As such, the as-fabricated paper-based sensor array exhibited an excellent discrimination ability in pH range of 1.00-13.60 with a high resolution of 0.20 pH unit, not only for standard pH buffer solutions but for real aqueous samples.

Simultaneous detection and identification of thiometon, phosalone, and prothioconazole pesticides using a nanoplasmonic sensor array

In this work, a colorimetric sensor array has been designed for the identification and discrimination of thiometon (TM) and phosalone (PS) as organophosphate pesticides and prothioconazole (PC) as a triazole pesticide. For this purpose, two different plasmonic nanoparticles including unmodified gold nanoparticles (AuNPs) and unmodified silver nanoparticles (AgNPs) were used as sensing elements. The principle of the proposed strategy relied on the aggregation AuNPs and AgNPs through the cross-reactive interaction between the target pesticides and plasmonic nanoparticles. Therefore, these aggregation-induced UV-Vis spectra changes were utilized to discriminate the target pesticides with the help of linear discriminant analysis (LDA). Besides, we have employed the bar plots and the heat maps as visual non-statistical methods to differentiate the pesticides in a wide range of concentrations (i.e., 20-5000 ng mL^-1). Multivariate calibration plots from partial least squares (PLS)- regression indicated that the responses linearly depend on the pesticide concentrations in the range of 100-1000 ng mL^-1 with the limit of detections (LOD) of 66.8, 68.3, and 41.4 ng mL^-1, for TM, PS, and PC, respectively. Finally, the potential applicability of the proposed sensor array has been evaluated for the detection and identification of the pesticides in the mixtures, water samples, and cucumber fruit.

Programmable Engineering of DNA-AuNP Encoders Integrated Multimodal Coupled Analysis for Precision Discrimination of Multiple Metal Ions

A cross-responsive strategy (CRS) based on gold nanoparticles (AuNPs) through attaching various recognition receptors on the surface of AuNPs for identifying multiple analytes is presented, and the detection throughput and overall identification accuracy are improved. However, the CRS's recognition receptor cannot get comprehensive information from the target analytes limited in number and type, which determines the overall identification accuracy. Therefore, the practicability of the CRS runs into a bottleneck. Herein, we report a programmable DNA-AuNP encoder combined with a multimodal coupled analysis algorithm for high-throughput detection and accurate analysis of multiple metal ions. The programmable DNA-AuNP encoder breaks through the limitation of the recognition receptor's quantity. Furthermore, the multimodal signals from target metal ion-induced DNA-AuNP aggregation are related to and observed in the ultraviolet absorbance spectrum, surface potential, and particle diameter. The multimodal coupled analysis algorithm can reflect comprehensive information on the target analyte more completely. Finally, this study provides a highly generic tool for the cross-responsive strategy.

Logic Gates Based on DNA Aptamers

DNA bio-computing is an emerging trend in modern science that is based on interactions among biomolecules. Special types of DNAs are aptamers that are capable of selectively forming complexes with target compounds. This review is devoted to a discussion of logic gates based on aptamers for the purposes of medicine and analytical chemistry. The review considers different approaches to the creation of logic gates and identifies the general algorithms of their creation, as well as describes the methods of obtaining an output signal which can be divided into optical and electrochemical. Aptameric logic gates based on DNA origami and DNA nanorobots are also shown. The information presented in this article can be useful when creating new logic gates using existing aptamers and aptamers that will be selected in the future.

Array-Based Discriminative Optical Biosensors for Identifying Multiple Proteins in Aqueous Solution and Biofluids

Identification of proteins is an important issue both in medical research and in clinical practice as a large number of proteins are closely related to various diseases. Optical sensor arrays with recognition ability have been flourished to apply for distinguishing multiple chemically or structurally similar analytes and analyzing unknown or mixed samples. This review gives an overview of the recent development of array-based discriminative optical biosensors for recognizing proteins and their applications in real samples. Based on the number of sensor elements and the complexity of constructing array-based discriminative systems, these biosensors can be divided into three categories, which include multi-element-based sensor arrays, environment-sensitive sensor arrays and multi-wavelength-based single sensing systems. For each strategy, the construction of sensing platform and detection mechanism are particularly introduced. Meanwhile, the differences and connections between different strategies were discussed. An understanding of these aspects may help to facilitate the development of novel discriminative biosensors and expand their application prospects.

A Critical Factor for Quantifying Proteins in Unmodified Gold Nanoparticles-Based Aptasensing: The Effect of pH

Unmodified gold nanoparticles (AuNPs)-based aptasensing (uGA) assay has been widely implemented in the determination of many different targets, but there are few reports on protein detection using uGA. Here, we designed a uGA assay for protein detection including the elimination of interfering proteins. Positively charged protein can be absorbed directly on the surface of AuNPs to form “protein corona”, which results in the aggregation of AuNPs even without salt addition, thereby preventing target protein detection. To overcome this problem, we systematically investigated the effect of modifying the pH of the solution during the uGA assay. A probe solution with a pH slightly higher than the isoelectric points (pI) of the target protein was optimal for protein detection in the uGA assay, allowing the aptamer to selectively detect the target protein. Three proteins (beta-lactoglobulin, lactoferrin, and lysozyme) with different pI were chosen as model proteins to validate our method. Positively charged interfering proteins (with pIs higher than the optimal pH) were removed by centrifugation of protein corona/AuNPs aggregates before the implementation of actual sample detection. Most importantly, the limit of detection (LOD) for all three model proteins was comparable to that of other methods, indicating the significance of modulating the pH. Moreover, choosing a suitable pH for a particular target protein was validated as a universal method, which is significant for developing a novel, simple, cost-effective uGA assay for protein detection.

Facile Approach to Fabricate a Chemical Sensor Array Based on Nanocurcumin-Metal Ions Aggregates: Detection and Identification of DNA Nucleobases

Here, a three-channel absorbance sensor array based on the nanocurcumin-metal ion (NCur-MI) aggregates is designed for the detection and identification of deoxyribonucleic acid nucleobases (DNA NBs) for the first time. For this purpose, the binding affinities of some of MIs (i.e., Co2+, Cr3+, Cu2+, Fe2+, Fe3+, Hg2+, Mn2+, Ni2+, V3+, and Zn2+) to the NCur to induce the aggregation were evaluated under various experimental conditions. Further studies reveal that in the presence of DNA NBs, the aggregates of NCur-Co2+, NCur-Ni2+, and NCur-Zn2+ show the diverse absorbance responses to the deaggregation of NCur depending on the binding affinity of each of DNA NBs to the metal ions Co2+, Ni2+, and Zn2+. These responses are distinguishable from one another. Thus, clear differentiation among the DNA NBs is achieved by linear discriminant analysis and hierarchical clustering analysis to generate clustering maps. The discriminatory capacity of the sensor array for the identification of the DNA NBs is tested in the ranges of 2.4-16 and 5.6-10.4 μM. Furthermore, a mixed set of the DNA NBs was prepared for multivariate multicomponent analysis. Finally, the practicability of the sensor array is confirmed by the discrimination of the DNA NBs in an animal DNA sample. It should be noted that the proposed array is the first example to fabricate an NCur-based sensor array for the simultaneous detection of DNA NBs.

New Sensors for Extracellular Vesicles: Insights on Constituent and Associated Biomarkers

Extracellular vesicles (EVs) are diverse, nanoscale membrane vesicles released by cells into the circulation. As an emerging class of circulating biomarkers, EVs contain a trove of molecular information and play important roles in mediating intercellular communication. These EV molecular cargoes are differentially organized in the vesicles; they could be inherited from the parent cells or bound to the EV membrane through surface interactions. While the inherited constituents could serve as cell surrogate biomarkers, extravesicular association could reflect structural states of the bound molecules, revealing distinct subpopulations with different biophysical and/or biochemical properties. Despite the clinical potential of EVs and their diverse contents, conventional sensing technologies have limited compatibility to reveal nanoscale EV features. Complementary analytical platforms are being developed to address these technical challenges and expand the biomedical applications of EVs, to establish novel correlations and empower new diagnostics. This article provides a perspective on recent developments in sensor technologies to profile the diverse contents-different molecular types, quantities, and organizational states-in extracellular vesicles.

Multichannel DNA Sensor Array Fingerprints Cell States and Identifies Pharmacological Effectors of Catabolic Processes

Cells at disease onset are often associated with subtle changes in the expression level of a single or few molecular components, making traditionally used biomarker-driven clinical diagnosis a challenging task. We demonstrate here the design of a DNA nanosensor array with multichannel output that identifies the normal or pathological state of a cell based on the alteration of its global proteomic signature. Fluorophore-encoded single-stranded DNA (ssDNA) strands were coupled via supramolecular interaction with a surface-functionalized gold nanoparticle quencher to generate this integrated sensor array. In this design, ssDNA sequences exhibit dual roles, where they provide differential affinities with the receptor gold nanoparticle as well as act as transducer elements. The unique interaction mode of the analyte molecules disrupts the noncovalent supramolecular complexation, generating simultaneous multichannel fluorescence output to enable signature-based analyte identification via a linear discriminant analysis-based machine learning algorithm. Different cell types, particularly normal and cancerous cells, were effectively distinguished using their fluorescent fingerprints. Additionally, this DNA sensor array displayed excellent sensitivity to identify cellular alterations associated with chemical modulation of catabolic processes. Importantly, pharmacological effectors, which could modulate autophagic flux, have been effectively distinguished by generating responses from their global protein signatures. Taken together, these studies demonstrate that our multichannel DNA nanosensor is well suited for rapid identification of subtle changes in a complex mixture and thus can be readily expanded for point-of-care clinical diagnosis, high-throughput drug screening, or predicting the therapeutic outcome from a limited sample volume.

Optical Fingerprints of Proteases and Their Inhibited Complexes Provided by Differential Cross-Reactivity of Fluorophore-Labeled Single-Stranded DNA

The detection of proteases and their complexes with inhibitor proteins is of great importance for diagnosis and medical-treatment applications. In this study, we report a fingerprint-based sensor using an array of single-stranded DNAs (ssDNAs) labeled with environment-responsive 3'-carboxytetramethylrhodamine (TAMRA) for the identification of proteases. Four TAMRA-modified ssDNAs with different sequences solubilized in two different buffer solutions were incorporated in an array that was capable of generating fluorescent fingerprints unique to the proteases through diverse cross-reactive interactions, allowing the discrimination of (i) 8 proteases and (ii) 12 different mixtures of trypsin and its inhibitor protein (α₁-antitrypsin) by multivariate analysis. Constructing an array with TAMRA-modified DNA aptamers that bind to different sites of human thrombin provides fluorescence fingerprints that reflect a reduction of the exposed surface area of thrombin upon complexation with antithrombin III, even in the presence of human serum. We finally demonstrate the potential of hybridization with complementary DNAs as an effective means to easily double the fingerprint information for proteases. Our approach based on the cross-reactive capability of ssDNAs enables high-throughput fingerprint-based sensing that can be flexibly designed and easily constructed, not only for the identification of a variety of proteins including proteases but also for the evaluation of their complexation ability.

Colorimetric sensor assay for discrimination of proteins based on exonuclease I-triggered aggregation of DNA-functionalized gold nanoparticles

Proteins play a key role in disease diagnosis, and protein discrimination is an important but difficult issue. Here, we report a novel strategy for improving protein discrimination through a facile colorimetric sensor array, which is based on DNA-gold nanoparticle (AuNP) conjugates manipulated by exonuclease I (Exo I). Different proteins exhibit diverse affinities toward the three DNAs, and the DNA-protein binding is resistant to the digestion of Exo I and protects the AuNPs from aggregation in high concentrations of NaCl media, forming distinct response patterns of the array. These response patterns as "fingerprints" can be acquired on the sensor array and then identified by linear discriminant analysis (LDA). The sensor array achieved the correct discrimination of 15 proteins at a 10 nM level in buffer solution and real serum samples. Also, the sensor array had the capability to discriminate individual proteins and the mixtures of them. Remarkably, the practicability of the sensor array was further confirmed by the identification of 35 unknown protein samples with 100% accuracy.

New application of old methods: Development of colorimetric sensor array based on Tollen's reagent for the discrimination of aldehydes based on Tollen's reagent

Qualitative and quantitative testing of aldehydes is meaningful for chemical toxin detection, food inspection, and disease monitoring. Herein, we reported a simple, accurate, and selective Tollen's reagent-based colorimetric sensor array for determination and detection of aldehydes. Three kinds of negatively charged gold nanoparticles (Au NPs) with different sizes (13, 22, and 40 nm) were synthesized and characterized by transmission electron microscopy and zeta potential measurement. In the presence of aldehydes, Ag+ from Tollen's reagent was attracted by the negative charge on the surface of Au NPs. Ag+ was reduced into Ag0 in situ, forming Au@Ag core-shell nanostructure and resulting in a significant color change. Detailed morphological and dimensional changes were observed by transmission electron microscopy. ΔRGB values (the value changes in the red, green, and blue color model) of Au NPs were captured as the optical signal for further data processing. Results of pattern recognition indicated the outstanding discrimination performance of the system for identification of aldehydes. Moreover, the array possessed quantitative detection capability for formaldehyde, selectivity, and reproducibility and thus has great potential in practical detection.

A colorimetric sensor array for detection and discrimination of antioxidants based on Ag nanoshell deposition on gold nanoparticle surfaces

There is growing interest in developing a high-performance sensor array for detection and discrimination of antioxidants owing to their widespread use and essential role in the human body. The present work unveils a novel colorimetric sensor array for colorimetric discrimination of antioxidants based on the red, green, and blue alteration (ΔRGB) pattern recognition. In this sensor array, three concentrations of AgNO3 were used as sensing elements, and gold nanoparticles (AuNPs) were employed as a colorimetric probe. In the presence of antioxidants, the sensor array produces unique colorimetric response patterns for the discrimination of these antioxidants due to different reactivities between three different concentrations of AgNO3 and each antioxidant, leading to deposition of different quantities of Ag nanoshells on the surface of AuNPs, enabling an excellent discrimination of six antioxidants (catechin, epigallocatechin 3-gallate, epicatechin, epigallocatechin, epicatechin 3-gallate, and gallocatechin) at a 20 nM level, when linear discriminant analysis (LDA), hierarchical cluster analysis (HCA), centroid diagram, spidergram, and color contour profiles were smartly combined. Furthermore, different concentrations of antioxidants and binary antioxidant mixtures, even ternary mixtures, could also be discriminated with this sensor array. Finally, the sensor array was successfully used for the discrimination of antioxidants in serum samples, demonstrating its potential applications in the diagnosis of antioxidant-related diseases.

Research advances of DNA aptasensors for foodborne pathogen detection

Aptamers, referring to single-stranded DNA or RNA molecules can specifically recognize and bind to their targets. Based on their excellent specificity, sensitivity, high affinity, and simplicity of modification, aptamers offer great potential for pathogen detection and biomolecular screening. This article reviews aptamer screening technologies and aptamer application technologies, including gold-nanoparticle lateral flow assays, fluorescence assays, electrochemical assays, colorimetric assays, and surface-enhanced Raman assays, in the detection of foodborne pathogens. Although notable progress (more rapid, sensitive, and accurate) has been achieved in the field, challenges and drawbacks in their applications still remain to be overcome.

Structural Elucidation and Ultrasensitive Analyses of Volatile Organic Compounds by Paper-Based Nano-Optoelectronic Noses

Paper-based optoelectronic noses (OENs) are being developed based on printing of organic and organometallic reagents on hydrophilic substrates that can visualize the odor of volatiles. In this work, we report for the first time the use of nanoparticles for fabrication of novel paper-based OENs, which represent much higher sensitivity and produce simple but discriminant colorimetric signature of volatile metabolomes. This nano-optoelectronic nose (NOEN) system, which is fabricated by dropping of gold and silver nanoparticles (each synthesized by 8 chemical species) on the paper, gives obvious colorimetric signatures for chemicals having individual or combined functional groups. Owning to their ultrasensitivity, these simple devices need very small amounts of analytes. These devices could detect and discriminate 45 volatile organic compounds in 9 chemical families including phenols, alchohols, ketones, aldehydes, amines, acids, esters, arenes, and hydrocarbons. In addition to excellent discrimination ability, this NOEN sensor shows ultrahigh sensitivity such that could determine volatile compounds with detection limits around or lower than 10 ppb. Moreover, it can be combined with multivariate calibration methods for quantitative analysis of a metabolite in a complex mixture.

Inorganic-Organic Hybrid Tongue-Mimic for Time-Resolved Luminescent Noninvasive Pattern and Chiral Recognition of Thiols in Biofluids toward Healthcare Monitoring

In this work, manganese(II)-doped zinc/germanium oxide nanoparticles (Mn@ZGNPs) have been hydrothermally synthesized to equip with appealing time-resolved luminescence (TRL). Interestingly, we reveal that they can be readily quenched ("turn off") via a facile surface coating with bioinspired polydopamine (PDA) polymerized from dopamine (DA), resulting from PDA-triggered TRL resonance energy transfer (TRL-RET). By integrated with the thiol-induced inhibition of PDA formation, an ingenious inorganic-organic hybrid tongue-mimic sensor array is thus unveiled for noninvasive pattern recognition of thiols in biofluids in a TRL-RET-reversed "turn on" format toward healthcare monitoring. The sensing principle is based on the new finding that there are differential inhibitions from thiols against the polymerization of DA with various concentrations. Furthermore, density function theory (DFT) studies excellently prove our sensing principle and experimental results, reinforcing the power of the presented system. More importantly, chiral recognition of varied concentrations and mixtures of cysteine enantiomers using our platform are also been demonstrated, promising its practical usage. This is a novel concept of inorganic-organic hybrid-based pattern and chiral recognition platform for TRL background-free sensing and would sprout more novel relevant strategies toward broader applications.

Nanozyme Sensor Arrays for Detecting Versatile Analytes from Small Molecules to Proteins and Cells

Nanozymes have emerged as promising alternatives to overcome the high cost and low stability of natural enzymes. Nanozymes with peroxidase-like activities have been studied to construct versatile biosensors by using specific biorecognition ligands (such as enzymes, antibodies, and aptamers) or molecularly imprinted polymers (MIPs). However, the use of bioligands compromises the high stability and low cost promise of nanozymes, while the MIPs may not be applicable to multiplex detection. To address these limitations, here we constructed the nanozyme sensor arrays based on peroxidase-like Pt, Ru, and Ir nanozymes. The cross-reactive nanozyme sensor arrays were successfully used for the detection of biothiols and proteins as well as the discrimination of cancer cells because of the differential nonspecific interactions between the components of the sensor arrays and the analytes. The usefulness of the nanozyme sensor arrays was further validated by the detection of blind unknown samples, where 28 of 30 biothiols and 42 of 45 proteins were correctly identified. Moreover, the practical application of the nanozyme sensor arrays was demonstrated by the successful discrimination of biothiols in serum and proteins in human urine.

Localized surface plasmon resonance based biosensing

INTRODUCTION

Bioanalytical sensing based on the principle of localized surface plasmon resonance experiences is currently an extremely rapid development. Novel sensors with new kinds of plasmonic transducers and innovative concepts for the signal development as well as read-out principles were identified. This review will give an overview of the development of this field. Areas covered: The focus is primarily on types of transducers by preparation or dimension, factors for optimal sensing concepts and the critical view of the usability of these devices as innovative sensors for bioanalytical applications. Expert commentary: Plasmonic sensor devices offer a high potential for future biosensing given that limiting factors such as long-time stability of the transducers, the required high sensitivity and the cost-efficient production are addressed. For higher sensitivity, the design of the sensor in shape and material has to be combined with optimal enhancement strategies. Plasmonic nanoparticles from bottom-up synthesis with a post-synthetic processing show a high potential for cost-efficient sensor production. Regarding the measurement principle, LSPRi offers a large potential for multiplex sensors and can provide a high-throughput as well as highly paralleled sensing. The main trends are expected towards optimal LSPR concepts which represent cost-efficient and robust point-of-care solutions, and the use of multiplexed devices for clinical applications.

Cationic polymer-based plasmonic sensor array that discriminates proteins

Breaking the restrictions of the lock-and-key sensing strategy which relies only on the most dominant interactions between the sensing element and target, here, we develop a colorimetric sensor array with three kinds of cationic polymers (polydiallyl dimethylammonium chloride (PDDA), chitosan (CTS), and cetyltrimethylammonium bromide (CTAB)) as nonspecific receptors.

Nanoparticle-based optical sensor arrays

As in many other methods that have integrated nanoparticles (NPs), the chemical nose/tongue strategy has also progressed greatly since the entrance of NPs into this field. The fascinating tunable physicochemical properties of NPs have made them powerful candidates for array-based sensing platforms and have enabled the development of real-time, sensitive and portable systems that are able to target complex mixtures of analytes. In particular, the unique optical properties of NPs have a key role in providing promising array-based sensing approaches. This review will describe the main aspects and processes of most common NP-based optical sensor arrays. The fundamental steps in the design of a sensor array together with details of each step would be provided. The review begins with the principles of optical sensor arrays and presents the concept of cross-reactivity as the main criterion in the selection of sensing elements. Changes in the absorption and emission properties of the assembled sensing elements are categorized into two main classes of optical signals (colorimetric and fluorometric). Popular chemometric methods used for analyzing the data acquired by a sensor array have also been briefly introduced. On the basis of the objective and the desired application, different types of plasmonic and fluorescent NP that possess unique opto-physical properties have been presented as available choices in the design of sensing elements. The vast number of applications of NP-based optical sensor arrays published throughout the literature have then been reviewed according to their mechanism of interaction and the type of optical signal. Finally, the remaining challenges and future directions in this topic have been highlighted.

Flexible Graphene-Based Wearable Gas and Chemical Sensors

Wearable electronics is expected to be one of the most active research areas in the next decade; therefore, nanomaterials possessing high carrier mobility, optical transparency, mechanical robustness and flexibility, lightweight, and environmental stability will be in immense demand. Graphene is one of the nanomaterials that fulfill all these requirements, along with other inherently unique properties and convenience to fabricate into different morphological nanostructures, from atomically thin single layers to nanoribbons. Graphene-based materials have also been investigated in sensor technologies, from chemical sensing to detection of cancer biomarkers. The progress of graphene-based flexible gas and chemical sensors in terms of material preparation, sensor fabrication, and their performance are reviewed here. The article provides a brief introduction to graphene-based materials and their potential applications in flexible and stretchable wearable electronic devices. The role of graphene in fabricating flexible gas sensors for the detection of various hazardous gases, including nitrogen dioxide (NO₂), ammonia (NH₃), hydrogen (H₂), hydrogen sulfide (H₂S), carbon dioxide (CO₂), sulfur dioxide (SO₂), and humidity in wearable technology, is discussed. In addition, applications of graphene-based materials are also summarized in detecting toxic heavy metal ions (Cd, Hg, Pb, Cr, Fe, Ni, Co, Cu, Ag), and volatile organic compounds (VOCs) including nitrobenzene, toluene, acetone, formaldehyde, amines, phenols, bisphenol A (BPA), explosives, chemical warfare agents, and environmental pollutants. The sensitivity, selectivity and strategies for excluding interferents are also discussed for graphene-based gas and chemical sensors. The challenges for developing future generation of flexible and stretchable sensors for wearable technology that would be usable for the Internet of Things (IoT) are also highlighted.

A Multi-Fluorescent DNA/Graphene Oxide Conjugate Sensor for Signature-Based Protein Discrimination

Signature-based protein sensing has recently emerged as a promising prospective alternative to conventional lock-and-key methods. However, most of the current examples require the measurement of optical signals from spatially-separated materials for the generation of signatures. Herein, we present a new approach for the construction of multi-fluorescent sensing systems with high accessibility and tunability, which allows generating protein fluorescent signatures from a single microplate well. This approach is based on conjugates between nano-graphene oxide (nGO) and three single-stranded DNAs (ssDNAs) that exhibit different sequences and fluorophores. Initially, the three fluorophore-modified ssDNAs were quenched simultaneously by binding to nGO. Subsequent addition of analyte proteins caused a partial recovery in fluorescent intensity of the individual ssDNAs. Based on this scheme, we have succeeded in acquiring fluorescence signatures unique to (i) ten proteins that differ with respect to pI and molecular weight and (ii) biochemical marker proteins in the presence of interferent human serum. Pattern-recognition methods demonstrated high levels of discrimination for this system. The high discriminatory power and simple format of this sensor system should enable an easy and fast evaluation of proteins and protein mixtures.