Universal sensor array for highly selective system identification using two-dimensional nanoparticles

Machine learning supported single-stranded DNA sensor array for multiple foodborne pathogenic and spoilage bacteria identification in milk

Ensuring food safety through rapid and accurate detection of pathogenic bacteria in food products is a critical challenge in the food supply chain. In this study, a non-specific optical sensor array was proposed for the identification of multiple pathogenic bacteria in contaminated milk samples. Fluorescence-labeled single-stranded DNA was efficiently quenched by two-dimensional nanoparticles and subsequently recovered by foreign biomolecules. The recovered fluorescence generated a unique fingerprint for each bacterial species, enabling the sensor array to identify eight bacteria (pathogenic and spoilage) within a few hours. Four traditional machine learning models and two artificial neural networks were applied for classification. The neural network showed a 93.8 % accuracy with a 30-min incubation. Extending the incubation to 120 min increased the accuracy of the multiplayer perceptron to 98.4 %. This sensor array is a novel, low-cost, and high-accuracy approach for the identification of multiple bacteria, providing an alternative to plate counting and ELISA methods.

Multistep Array-Based Sensing of Bioanalytes Using Modified MoS2, Fluorescence Proteins, and Cucurbituril

One pot sensor by multiplexing in the array is an attractive system for rapid discrimination of multiple analytes. Multiplexing can be achieved in two ways, i.e., using multiple signal transducers or adding sequential agents to the sensor media. Herein, we have used a combination of both multichannel and sequential ON-OFF strategies for the discrimination of different bioanalytes. The sensor array was constructed by implementing positively charged MoS2 as a receptor and different fluorescent proteins possessing distinguishable emission profiles as signal transducers. The sensing setup was constructed with the interaction between oppositely charged MoS2 and the host-guest combination between a cationic headgroup of MoS2 and Cucurbit [7] uril (CB7) to alter the fluorescence of signal transducers in situ noncovalently. Electrodynamic analysis and optical assays suggest that the electrostatic interaction played a major role in the modulation of the fluorescence outcomes in the array. Both cationic and anionic proteins were discriminated at a 50 nM concentration. The detection limit of the sensor array by using β-gal protein was found to be 1 nM. The sensor array was further implemented for the discrimination of normal and diseased cell lines and lysates, which indicates the versatile detection ability of this reported sensor array.

Chemical tongues as multipurpose bioanalytical tools for the characterization of complex biological samples

Chemical tongues are emerging powerful bioanalytical tools that mimic the mechanism of the human taste system to recognize the comprehensive characteristics of complex biological samples. By using an array of chromogenic or fluorogenic probes that interact non-specifically with various components in the samples, this tool generates unique colorimetric or fluorescence patterns that reflect the biological composition of a sample. These patterns are then analyzed using multivariate analysis or machine learning to distinguish and classify the samples. This review focuses on our efforts to provide an overview of the fundamental principles of chemical tongues, probe design, and their applications as versatile tools for analyzing proteins, cells, and bacteria in biological samples. Compared to conventional methods that rely on specific targeting (e.g., antibodies or enzymes) or comprehensive omics analyses, chemical tongues offer advantages in terms of cost and the ability to analyze samples without the need for specific biomarkers. The complementary use of chemical tongues and conventional methods is expected to enable a more detailed understanding of biological samples and lead to the elucidation of new biological phenomena.

Regulation of Two-Dimensional Platelet Micelles with Tunable Core Composition Distribution via Coassembly Seeded Growth Approach

Seeded growth termed "living" crystallization-driven self-assembly (CDSA) has been identified as a powerful method to create one- or two-dimensional nanoparticles. Epitaxial crystallization is usually regarded as the growth mechanism for the formation of uniform micelles. From this perspective, the unimer depositing rate is largely related to the crystallization temperature, which is a key factor to determine the crystallization rate and regulate the core composition distribution among nanoparticles. In the present work, the coassembly of two distinct crystallizable polymers is explored in detail in a one-pot seeded growth protocol. Results have shown that polylactone containing a larger number of methylene groups (-CH2-) in their repeating units such as poly(η-octalactone) (POL) has a faster crystallization rate compared to poly(ε-caprolactone) (PCL) with a smaller number of -CH2- at ambient temperature (25 °C), thus a block or blocky platelet structure with heterogeneous composition distribution is formed. In contrast, when the crystallization temperature decreases to 4 °C, the difference of crystallization rate between both cores become negligible. Consequently, a completely random component distribution within 2D platelets is observed. Moreover, we also reveal that the core component of seed micelles is also paramount for the coassembly seeded growth, and a unique structure of flower-like platelet micelle is created from the coassembly of PCL/POL using POL core-forming seeds. This study on the formation of platelet micelles by one-pot seeded growth using two crystallizable components offers a considerable scope for the design of 2D polymer nanomaterials with a controlled core component distribution.

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.

Dual-Emission Single Sensing Element-Assembled Fluorescent Sensor Arrays for the Rapid Discrimination of Multiple Surfactants in Environments

Surfactants are considered as typical emerging pollutants, their extensive use of in disinfectants has hugely threatened the ecosystem and human health, particularly during the pandemic of coronavirus disease-19 (COVID-19), whereas the rapid discrimination of multiple surfactants in environments is still a great challenge. Herein, we designed a fluorescent sensor array based on luminescent metal-organic frameworks (UiO-66-NH2@Au NCs) for the specific discrimination of six surfactants (AOS, SDS, SDSO, MES, SDBS, and Tween-20). Wherein, UiO-66-NH2@Au NCs were fabricated by integrating UiO-66-NH2 (2-aminoterephthalic acid-anchored-MOFs based on zirconium ions) with gold nanoclusters (Au NCs), which exhibited a dual-emission features, showing good luminescence. Interestingly, due to the interactions of surfactants and UiO-66-NH2@Au NCs, the surfactants can differentially regulate the fluorescence property of UiO-66-NH2@Au NCs, producing diverse fluorescent "fingerprints", which were further identified by pattern recognition methods. The proposed fluorescence sensor array achieved 100% accuracy in identifying various surfactants and multicomponent mixtures, with the detection limit in the range of 0.0032 to 0.0315 mM for six pollutants, which was successfully employed in the discrimination of surfactants in real environmental waters. More importantly, our findings provided a new avenue in rapid detection of surfactants, rendering a promising technique for environmental monitoring against trace multicontaminants.

An aptamer array for discriminating tetracycline antibiotics based on binding-enhanced intrinsic fluorescence

Tetracyclines are a class of antibiotics with a similar four-ringed structure. Due to this structural similarity, they are not easily differentiated from each other. We recently selected aptamers using oxytetracycline as a target and focused on an aptamer named OTC5, which has similar affinities for oxytetracycline (OTC), tetracycline (TC), and doxycycline (DOX). Tetracyclines exhibit an intrinsic fluorescence that is enhanced upon aptamer binding, allowing convenient binding assays and label-free detection. In this study, we analyzed the top 100 sequences from the previous selection library. Three other sequences were found to differentiate between different tetracyclines (OTC, DOX, and TC) by the selective enhancement of their intrinsic fluorescence. Among them, the OTC43 aptamer was more selective for OTC with a limit of detection (LOD) of 0.7 nM OTC, OTC22 was more selective for DOX (LOD 0.4 nM), and OTC2 was more selective for TC (0.3 nM). Using these three aptamers to form a sensor array, principal component analysis was able to discriminate between the three tetracyclines from each other and from the other molecules. This group of aptamers could be useful as probes for the detection of tetracycline antibiotics.

Iron oxides based nanozyme sensor arrays for the detection of active substances in licorice

With the increasing applications of traditional Chinese medicines worldwide, authenticity identification and quality control are significant for them to go global. Licorice is a kind of medicinal material with various functions and wide applications. In this work, colorimetric sensor arrays based on iron oxide nanozymes were constructed to discriminate active indicators in licorice. Fe₂O₃, Fe₃O₄, and His-Fe₃O₄ nanoparticles were synthesized by a hydrothermal method, possessing excellent peroxidase-like activity that can catalyze the oxidation of 3,3',5,5' -tetramethylbenzidine (TMB) in the presence of H₂O₂ to produce a blue product. When licorice active substances were introduced in the reaction system, they showed competitive effect on peroxidase-mimicking activity of nanozymes, resulting in inhibitory effect on the oxidation of TMB. Based on this principle, four licorice active substances including glycyrrhizic acid, liquiritin, licochalcone A, and isolicoflavonol with the concentration ranging from 1 μM to 200 μM were successfully discriminated by the proposed sensor arrays. This work supplies a low cost, rapid and accurate method for multiplex discrimination of active substances to guarantee the authenticity and quality of licorice, which is also expected to be applied to distinguish other substances.

Ligand Exchange on MoS2 Nanosheets: Applications in Array-Based Sensing and Drug Delivery

Two-dimensional MoS2 nanosheets (2D-MoS2) have been widely used in many biological applications due to their distinctive physicochemical properties. Further, the development of surface modification using thiolated ligands allows us to use them for many specific applications. But the effect of possible ligand exchange on 2D-MoS2 has never been explored, which can play an important role in diverse biological applications. In this study, we have observed the ligand-exchange phenomenon on 2D-MoS2 in the presence of different thiolated ligands. The initial study proceeded with boron-dipyrromethene (BODIPY) functionalized MoS2 with different concentrations of glutathione (GSH), which is the most abundant thiol species in the cytoplasm of various cancer cells. It was found that in the presence of GSH the fluorescence of BODIPY can be regenerated, which is time and concentration dependent. We have also examined this phenomenon with different thiol ligands and transition-metal dichalcogenides (TMDs). We observed a variable rate of ligand exchange in different solvents, surface functionality, and receptor environments that helped us to construct sensor arrays. Interestingly, a ligand-exchange process was not observed in the presence of dithiols. Further, this concept was applied to a cancerous cell line for in vitro delivery. We found that BODIPY-functionalized 2D-MoS2 undergoes thiol exchange by intracellular GSH and subsequently enhanced the fluorescence in the cytoplasm of cancer cells. This strategy can be applied to the development of 2D-TMD-based materials for various biological applications related to ligand exchange.

Direct discrimination of cell surface glycosylation signatures using a single pH-responsive boronic acid-functionalized polymer

Cell surface glycans serve fundamental roles in many biological processes, including cell-cell interaction, pathogen infection, and cancer metastasis. Cancer cell surface have alternative glycosylation to healthy cells, making these changes useful hallmarks of cancer. However, the diversity of glycan structures makes glycosylation profiling very challenging, with glycan 'fingerprints' providing an important tool for assessing cell state. In this work, we utilized the pH-responsive differential binding of boronic acid (BA) moieties with cell surface glycans to generate a high-content six-channel BA-based sensor array that uses a single polymer to distinguish mammalian cell types. This sensing platform provided efficient discrimination of cancer cells and readily discriminated between Chinese hamster ovary (CHO) glycomutants, providing evidence that discrimination is glycan-driven. The BA-functionalized polymer sensor array is readily scalable, providing access to new diagnostic and therapeutic strategies for cell surface glycosylation-associated diseases.

Interactions of proteins with metal-based nanoparticles from a point of view of analytical chemistry - Challenges and opportunities

Interactions of proteins with nanomaterials draw attention of many research groups interested in fundamental phenomena. However, alongside with valuable information regarding physicochemical aspects of such processes and their mechanisms, they more and more often prove to be useful from a point of view of bioanalytics. Deliberate use of processes based on adsorption of proteins on nanoparticles (or vice versa) allows for a development of new analytical methods and improvement of the existing ones. It also leads to obtaining of nanoparticles of desired properties and functionalities, which can be used as elements of analytical tools for various applications. Due to interactions with nanoparticles, proteins can also gain new functionalities or lose their interfering potential, which from perspective of bioanalytics seems to be very inviting and attractive. In the framework of this article we will discuss the bioanalytical potential of interactions of proteins with a chosen group of nanoparticles, and implementation of so driven processes for biosensing. Moreover, we will show both positive and negative (opportunities and challenges) aspects resulting from the presence of proteins in media/samples containing metal-based nanoparticles or their precursors.

A machine learning approach-based array sensor for rapidly predicting the mechanisms of action of antibacterial compounds

Rapid and accurate identification of the mechanisms of action (MoAs) of antibacterial compounds remains a challenge for the development of antibacterial compounds. Computational inference methods for determining the MoAs of antibacterial compounds have been developed in recent years. In particular, approaches combining machine learning technology enable precisely recognizing the MoA of antibacterial compounds. However, these methods heavily rely on the big data resulting from multiplexed experiments. As such, these approaches tend to produce minimal throughput and are not comprehensive enough to be adapted to widespread industrial applications. Here, we present a machine learning approach based on a customized array sensor for directly identifying the MoAs of antibacterial compounds. The array sensor consists of different two-dimensional nanomaterial fluorescence quenchers with different fluorescence-labeled single-stranded DNAs (ssDNAs). By mapping the subtle difference of the physicochemical properties on the bacterial surface treated with different antibacterial compound stimuli, the array sensor ensures visualizing the recognition process. Moreover, the customized array sensor produces a high volume of the MoA database, overcoming the dependence on big data. We further use the array sensor to build a chemical-response unique "fingerprint" database of MoAs. By combining a neural network-based genetic algorithm (NNGA), we rapidly discriminate the MoAs of four antibiotics with an overall accuracy of 100%. Furthermore, a new screening antibacterial peptide has been discovered and evaluated by our approach for determining the MoA with high accuracy proven by other techniques.

Algorithmically Guided Optical Nanosensor Selector (AGONS): Guiding Data Acquisition, Processing, and Discrimination for Biological Sampling

Here, we report a biomarker-free detection of various biological targets through a programmed machine learning algorithm and an automated computational selection process termed algorithmically guided optical nanosensor selector (AGONS). The optical data processed/used by algorithms are obtained through a nanosensor array selected from a library of nanosensors through AGONS. The nanosensors are assembled using two-dimensional nanoparticles (2D-nps) and fluorescently labeled single-stranded DNAs (F-ssDNAs) with random sequences. Both 2D-np and F-ssDNA components are cost-efficient and easy to synthesize, allowing for scaled-up data collection essential for machine learning modeling. The nanosensor library was subjected to various target groups, including proteins, breast cancer cells, and lethal-7 (let-7) miRNA mimics. We have demonstrated that AGONS could select the most essential nanosensors while achieving 100% predictive accuracy in all cases. With this approach, we demonstrate that machine learning can guide the design of nanosensor arrays with greater predictive accuracy while minimizing manpower, material cost, computational resources, instrumentation usage, and time. The biomarker-free detection attribute makes this approach readily available for biological targets without any detectable biomarker. We believe that AGONS can guide optical nanosensor array setups, opening broader opportunities through a biomarker-free detection approach for most challenging biological targets.

A sensor array based on DNA-wrapped bimetallic zeolitic imidazolate frameworks for detection of ATP hydrolysis products

Most current biosensors were designed for the detection of individual analytes, or a group of chemically similar analytes. We reason that sensors designed to track both reactants and products might be useful for following chemical reactions. Adenosine triphosphate (ATP) is a key biomolecule that participates in various biochemical reactions, and its hydrolysis plays a fundamental role in life. ATP can be converted to adenosine diphosphate (ADP) and inorganic phosphate (Pi) via the dephosphorylation process. ATP can also be hydrolyzed to adenosine monophosphate (AMP) and pyrophosphate (PPi) through depyrophosphorylation, depending on where the bond is cleaved. The detection of ATP-related hydrolysates would enable a better understanding of the different reaction pathways with a high level of robustness and confidence. Herein, we prepared a fluorescent sensor array based on a series of bimetallic zeolite imidazole frameworks M/ZIF-8 (M = Ni, Mn, Cu) and ZIF-67 to discriminate ATP hydrolysis and detect ATP hydrolysis related analytes. A fluorescently-labeled DNA oligonucleotide was used for signaling. Interestingly, Cu/ZIF-8 exhibited an ultrahigh selectivity for recognizing pyrophosphate with a detection limit of 2.5 μM. Moreover, the practicality of this sensor array was demonstrated in fetal bovine serum, clearly discriminating ATP hydrolysis products.

A peroxidase-like activity-based colorimetric sensor array of noble metal nanozymes to discriminate heavy metal ions

Heavy metal ions (HMIs), including Cu²⁺, Ag⁺, Cd²⁺, Hg²⁺, and Pb²⁺ from the environment pose a threat to human beings and can cause a series of life-threatening diseases. Therefore, colorimetric sensors with convenience and flexibility for HMI discrimination are still required. To provide a solution, a peroxidase-like activity-based colorimetric sensor array of citrate-capped noble metal nanozymes (osmium, platinum, and gold) has been fabricated. Some studies reported that some HMIs could interact with the noble metal nanozymes leading to a change in their peroxidase-like activity. This phenomenon was confirmed in our work. Based on this principle, different concentrations of HMIs (Cu²⁺, Ag⁺, Cd²⁺, Hg²⁺, and Pb²⁺) were discriminated. Moreover, their practical application has been tested by discriminating HMIs in tap water and SiYu lake water. What is more, as an example of the validity of our method to quantify HMIs at nanomolar concentrations, the LOD of Hg²⁺ was presented. To sum up, our study not only demonstrates the differentiation ability of this nanozyme sensor array but also gives hints for using nanozyme sensor arrays for further applications.

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.

Surface-enhanced Raman spectroscopy for bioanalysis and diagnosis

In recent years, bioanalytical surface-enhanced Raman spectroscopy (SERS) has blossomed into a fast-growing research area. Owing to its high sensitivity and outstanding multiplexing ability, SERS is an effective analytical technique that has excellent potential in bioanalysis and diagnosis, as demonstrated by its increasing applications in vivo. SERS allows the rapid detection of molecular species based on direct and indirect strategies. Because it benefits from the tunable surface properties of nanostructures, it finds a broad range of applications with clinical relevance, such as biological sensing, drug delivery and live cell imaging assays. Of particular interest are early-stage-cancer detection and the fast detection of pathogens. Here, we present a comprehensive survey of SERS-based assays, from basic considerations to bioanalytical applications. Our main focus is on SERS-based pathogen detection methods as point-of-care solutions for early bacterial infection detection and chronic disease diagnosis. Additionally, various promising in vivo applications of SERS are surveyed. Furthermore, we provide a brief outlook of recent endeavours and we discuss future prospects and limitations for SERS, as a reliable approach for rapid and sensitive bioanalysis and diagnosis.

Metal-organic framework/3,3',5,5'-tetramethylbenzidine based multidimensional spectral array platform for sensitive discrimination of protein phosphorylation

A multifunctional metal-organic framework (MOF) hybrid Zr-FeTCPP-MOF is fabricated with 2-aminoterephthalic acid (NH₂-BDC) and Fe (III) meso-Tetra (4-carboxyphenyl) porphine chloride (FeTCPPCl) participating in the coordination to Zr₆ clusters via one-pot hydrothermal method. The adsorption of phosphoproteins on the surface of Zr-FeTCPP-MOF hybrid cause the chances on the absorbance (Abs), fluorescence (FL) and resonance light scattering (RLS) signals of Zr-FeTCPP-MOF/3,3',5,5'-Tetramethylbenzidine (TMB) system, and an array sensing platform is successfully built for sensitive identification of protein phosphorylation based on the three-dimensional spectral changes of MOF/TMB sensing system induced by the variations on the structure, size, and phosphorylation site of phosphoproteins. This array sensing system is robust in recognizing different phosphoprotein species, and shows high sensitivity in discriminating similar phosphoproteins of different phosphorylation distribution, i.e., caseins (α-, β- and κ-cas). The detection limit of this array sensing platform to individual phosphoprotein is low down to 5 nM. The practical application of this MOF/TMB-base sensing system is substantially demonstrated by identifying tau peptides with different phosphorylation distribution, and distinguishing cancer cells of abnormal phosphorylations from normal cells. This work proves the reliability, sensitivity, and practicality of the MOF/TMB-base sensing system platform for the diagnosis of phosphorylation-related diseases in clinical trials.

Machine Learning-Assisted Array-Based Detection of Proteins in Serum Using Functionalized MoS2 Nanosheets and Green Fluorescent Protein Conjugates

Abnormal concentrations of a specific protein or the presence of some biomarker proteins may indicate life-threatening diseases. Pattern-based detection of specific analytes using affinity-regulated receptors is one of the potential alternatives to specific antigen-antibody-based detection. In this report, we have schemed a sensor array by using various functionalized two-dimensional (2D)-MoS2 nanosheets and green fluorescent protein (GFP) as the receptor and the signal transducer, respectively. Two-dimensional MoS2 has been used as a promising candidate for recognition of the bioanalytes because of its high surface-to-volume ratio compared to those of other nanomaterials. Easy surface tunability of this material provides additional advantages to analyze the target of interest. The optimized 2D-MoS2-GFP conjugates are able to discriminate 15 different proteins at 50 nM concentration with a detection limit of 1 nM. Moreover, proteins in the binary mixture and in the presence of serum were discriminated successfully. Ten different proteins in serum media at relevant concentrations were classified successfully with 100% jackknifed classification accuracy, which proves the potentiality of the above system. We have also implemented and discussed the implication of using different machine learning models on the pattern recognition problem associated with array-based sensing.

Machine-Learning Single-Stranded DNA Nanoparticles for Bacterial Analysis

A two-dimensional nanoparticle-single-stranded DNA (ssDNA) array has been assembled for the detection of bacterial species using machine-learning (ML) algorithms. Out of 60 unknowns prepared from bacterial lysates, 54 unknowns were predicted correctly. Furthermore, the nanosensor array, supported by ML algorithms, was able to distinguish wild-type Escherichia coli from its mutant by a single gene difference. In addition, the nanosensor array was able to distinguish untreated wild-type E. coli from those treated with antimicrobial drugs. This work demonstrates the potential of nanoparticle-ssDNA arrays and ML algorithms for the discrimination and identification of complex biological matrixes.

Protein discrimination based on DNA induced perylene probe self-assembly

The development of a simple and effective method for the highly sensitive and selective discrimination of proteins is a subject of enormous interest. Herein, we report the construction of a novel fluorescence detection method based on a perylene probe for the highly efficient discrimination of multiple proteins. Single-stranded DNA (ssDNA) could induce aggregation of the perylene probe which caused quenching of probe fluorescence. After the addition of a protein, the protein could interact with the ssDNA-probe assembly complex with "turn-on" or further "turn-off" fluorescence response. A sensor array was designed based on the above phenomena which could realize the successful discrimination of proteins with 100% accuracy of cross validation. Nine representative proteins were successfully recognized. Moreover, it was observed that a protein could induce characteristic effect on the DNA-probe assembly with varying pH of assay buffer. Thus, different proteins showed unique fluorescence response towards assay buffers having different pH values. The assay buffer pH was then utilized as a sensing channel. Based on Linear Discriminant Analysis (LDA) nine proteins were successfully discriminated at the nanomolar concentration with 100% accuracy of cross validation. Furthermore, the sensor array also demonstrated differentiation of the nine proteins regardless of their concentration. The developed sensor array could also detect the proteins with great precision in human urine sample at a quite low concentration, which suggests its practical applicability for analysis of biological fluids.

A Multichannel Pattern-Recognition-Based Protein Sensor with a Fluorophore-Conjugated Single-Stranded DNA Set

Recently, pattern-recognition-based protein sensing has received considerable attention because it offers unique opportunities that complement more conventional antibody-based detection methods. Here, we report a multichannel pattern-recognition-based sensor using a set of fluorophore-conjugated single-stranded DNAs (ssDNAs), which can detect various proteins. Three different fluorophore-conjugated ssDNAs were placed into a single microplate well together with a target protein, and the generated optical response pattern that corresponds to each environment-sensitive fluorophore was read via multiple detection channels. Multivariate analysis of the resulting optical response patterns allowed an accurate detection of eight different proteases, indicating that fluorescence signal acquisition from a single compartment containing a mixture of ssDNAs is an effective strategy for the characterization of the target proteins. Additionally, the sensor could identify proteins, which are potential targets for disease diagnosis, in a protease and inhibitor mixture of different composition ratios. As our sensor benefits from simple construction and measurement procedures, and uses accessible materials, it offers a rapid and simple platform for the detection of proteins.

Pattern-recognition-based Sensor Arrays for Cell Characterization: From Materials and Data Analyses to Biomedical Applications

To capture a broader scope of complex biological phenomena, alternatives to conventional sensing based on specificity for cell detection and characterization are needed. Pattern-recognition-based sensing is an analytical method designed to mimic mammalian sensory systems for analyte identification based on the pattern recognition of multivariate data, which are generated using an array of multiple probes that cross-reactively interact with analytes. This sensing approach is significantly different from conventional specific cell sensing based on highly specific probes, including antibodies against biomarkers. Encouraged by the advantages of this technique, such as the simplicity, rapidity, and tunability of the systems without requiring a priori knowledge of biomarkers, numerous sensor arrays have been developed over the past decade and used in a variety of cell sensing applications; these include disease diagnosis, drug discovery, and fundamental research. This review summarizes recent progress in pattern-recognition-based cell sensing, with a particular focus on guidelines for designing materials and arrays, techniques for analyzing response patterns, and applications of sensor systems that are focused primarily for the biomedical field.

Impedimetric electronic tongue based on molybdenum disulfide and graphene oxide for monitoring antibiotics in liquid media

Antibiotics are considered emerging pollutants which indiscriminate use has led to the development of antibiotic-resistant bacteria, while their improper disposal has caused adverse effects to the environment and human health. Thus, the development of devices or techniques capable of detecting antibiotics with high sensitivity, low detection limits, and reasonable cost becomes of prime importance. In this work, an electronic tongue (e-tongue) based on molybdenum disulfide (MoS₂) and graphene oxide (GO) was developed and employed to detect four distinct antibiotics, namely cloxacillin benzathine, erythromycin, streptomycin sulfate, and tetracycline hydrochloride. The five sensing units of the e-tongue were obtained using the drop-casting method to modify gold interdigitated electrodes with MoS₂ and GO. Using Principal Component Analysis to process the experimental data allowed the e-tongue to recognize samples contaminated with distinct antibiotics at varied concentrations from 0.5 to 5.0 nmol L^-1. Analyses with real samples were also performed using river water and human urine and the electronic tongue was able to differentiate the samples at a nanomolar level. The proposed system represents a sensitive and low-cost alternative for antibiotic analyses in different liquid media.

Applications of Two-Dimensional Nanomaterials in Breast Cancer Theranostics

Breast cancer is the leading cause of cancer-related mortality among women. Early stage diagnosis and treatment of this cancer are crucial to patients' survival. In addition, it is important to avoid severe side effects during the process of conventional treatments (surgery, chemotherapy, hormonal therapy, and targeted therapy) and increase the patients' quality of life. Over the past decade, nanomaterials of all kinds have shown excellent prospects in different aspects of oncology. Among them, two-dimensional (2D) nanomaterials are unique due to their physical and chemical properties. The functional variability of 2D nanomaterials stems from their large specific surface area as well as the diversity of composition, electronic configurations, interlayer forces, surface functionalities, and charges. In this review, the current status of 2D nanomaterials in breast cancer diagnosis and therapy is reviewed. In this respect, sensing of the tumor biomarkers, imaging, therapy, and theranostics are discussed. The ever-growing 2D nanomaterials are building blocks for the development of a myriad of nanotheranostics. Accordingly, there is the possibility to explore yet novel properties, biological effects, and oncological applications.

Gate-tunable gas sensing behaviors in air-stable ambipolar organic thin-film transistors

Chemiresistive gas sensors, which exploit their electrical resistance in response to changes in nearby gas environments, usually achieve selective gas detection using multi-element sensor arrays. As large numbers of sensors are required, they often suffer from complex and high-cost fabrication. Here, we demonstrate an ambipolar organic thin-film transistor as a potential multi-gas sensing device utilizing gate-tunable gas sensing behaviors. Combining behaviors of both electron and hole carriers in a single device, the proposed device showed dynamic changes depending on gate biases and properties of target gases. As a result, the gas response as a function of gate biases exhibits a unique pattern towards a specific gas as well as its concentrations, which is very different from conventional unipolar organic thin-film transistors. In addition, our device showed an excellent air-stable characteristic compared to typical ambipolar transistors, providing great potential for practical use in the future.

Ambipolar organic field effect transistor shows a great potential to be used for multi-gas sensing device utilizing gate-tunable gas sensing behaviors.

Aggregation-induced emission based one-step “lighting up” sensor array for rapid protein identification

Based on the distinct fingerprint-like fluorescence responses generated by different electrostatic and hydrophobic interactions, a “lighting up” aggregation-induced emission (AIE) sensor array was developed for rapid protein discrimination.

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.

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.

Fluorescent sensor array for separation-free dopamine analogue discrimination via polyethyleneimine-mediated self-polymerization reaction

The effective discrimination of dopamine (DA) analogues is an enduring challenge because of their very tiny structural differences, and thus a separation technique is generally required during the conventional analysis. In this study, a hyperbranched polyethyleneimine (hPEI)-based fluorescent sensor array has been constructed for the separation-free and effective differentiation of four DA analogues. The discrimination includes two steps: firstly, the formation of fluorescent polymer nanoparticles (FPNs) with diverse emission profiles via hPEI-mediated self-polymerization reaction of DA analogues and secondly, the linear discriminant analysis of fluorescence patterns of the formed FPNs for the differentiation of DA analogues. The hPEI-assisted self-polymerization reaction of DA analogues and substitution group mediated optical properties of the resulted FPNs enable an excellent discrimination of four DA analogues at a concentration of 1.0 μM when linear discriminant analysis and hierarchical cluster analysis are smartly combined. Additionally, binary, tertiary and even quaternary mixtures of analogues can also be well distinguished with the proposed sensor array. The practicability of this established sensor array is validated by a high accuracy (100%) evaluation of 88 blind samples containing a single analogue or a mixture of two, three or four analogues.

Adsorption of Arsenite on Gold Nanoparticles Studied with DNA Oligonucleotide Probes

Gold nanoparticles (AuNPs) have been extensively used for detecting arsenite, As(III). Many methods rely on a DNA aptamer that claimed to bind specifically to inorganic arsenic. In these cases, the focus was on arsenic binding to the aptamer, while the potential interactions between As(III) and the AuNP surface were ignored. Herein, a set of spectroscopic and isothermal titration calorimetry (ITC) experiments were conducted to measure the adsorption of As(III) by AuNPs and its competition with DNA adsorption. With 10 mM As(III), 18% of adsorbed DNA was displaced from AuNPs, while preadsorption of only 20 μM As(III) inhibited DNA adsorption by around 50%. The affinity of As(III) on AuNPs is comparable to Br^- and guanosine. ITC and Raman spectroscopy both indicated that only As(III) can be adsorbed, while As(V) had no measurable interactions with the AuNPs. Based on this understanding, a random DNA sequence was used and a similar colorimetric response in the presence of As(III) was observed. This study confirmed the affinity between As(III) and the gold surface. The As(III)/gold interaction is strong enough to affect DNA adsorption, and care should be taken to interpret the observations based on the color change of AuNPs for the detection of As(III).

Colorimetric Sensor Arrays for Antioxidant Discrimination Based on the Inhibition of the Oxidation Reaction between 3,3',5,5'-Tetramethylbenzidine and Hydrogen Peroxides

The discrimination of antioxidants is of great significance because of their essential roles in various biological processes and many diseases. Compared with the traditional lock-key sensing mode for single target detection at a time, sensor arrays can discriminate various antioxidants simultaneously. Nanomaterial-based sensor arrays have shown great promise for antioxidant discrimination; however, as far as it is known, none of them have been reported for discriminating antioxidants based on the catalytic reaction of intrinsic peroxidase-like activity of two-dimensional nanomaterials. To fill the gap, we herein unveil a colorimetric (e.g., UV-vis absorption) approach for antioxidant discrimination based on the three nanomaterial [graphene oxide, molybdenum disulfide (MoS₂), and tungsten disulfide (WS₂)]-catalyzed 3,3',5,5'-tetramethylbenzidine (TMB)-hydrogen peroxide (H₂O₂) reaction system. In this sensor array, the antioxidants inhibit the reaction between TMB and H₂O₂, resulting in different colorimetric response patterns. The obtained patterns for five antioxidants, including ascorbic acid, cysteine, melatonin, uric acid, and glutathione (GSH), at the 60 nM level, were successfully discriminated using linear discriminant analysis both in buffer and serum samples.

A pH-based sensor array for the detection and identification of proteins using CdSe/ZnS quantum dots as an indicator

A novel and simple fluorescence sensor array was developed for the detection and identification of proteins using pH buffer solutions as sensing elements.

DNA-Functionalized Nanoceria for Probing Oxidation of Phosphorus Compounds

Chemical reactions without an obvious optical signal change, such as fluorescence or color, are difficult to monitor. Often, more advanced analytical techniques such as high-performance liquid chromatography and mass spectroscopy are needed. It would be useful to convert such reactions to those with changes in optical signals. In this work, we demonstrate that fluorescently labeled DNA oligonucleotides adsorbed on nanomaterials can probe such reactions, and oxidation of phosphorus-containing species was used as an example. Various metal oxides were tested, and CeO2 nanoparticles were found to be the most efficient for this purpose. Among phosphate, phosphite, and hypophosphite, only phosphate produced a large signal, indicating its strongest adsorption on CeO2 to displace the DNA. This was further used to screen oxidation agents to convert lower oxidation-state compounds to phosphate, and bleach was found to be able to oxidize phosphite. Canonical discriminant analysis was performed to discriminate various phosphorus species using a sensor array containing different metal oxides. On the basis of this, glyphosate was studied for its adsorption and oxidation. Although this method is not specific enough for selective biosensors, it is useful as a tool to produce sensitive optical signals to follow important chemical transformations.

Polyphenol-Assisted Exfoliation of Transition Metal Dichalcogenides into Nanosheets as Photothermal Nanocarriers for Enhanced Antibiofilm Activity

Transition metal dichalcogenide (TMD) nanosheets have evoked enormous research enthusiasm and have shown increased potentials in the biomedical field. However, a great challenge lies in high-throughput, large-scale, and eco-friendly preparation of TMD nanosheet dispersions with high quality. Herein, we report a universal polyphenol-assisted strategy to facilely exfoliate various TMDs into monolayer or few-layer nanosheets. By optimizing the exfoliation condition of molybdenum disulfide (MoS₂), the yield and concentration of as-exfoliated nanosheets are up to 60.5% and 1.21 mg/mL, respectively. This is the most efficient aqueous exfoliation method at present and is versatile for the choices of polyphenols and TMD nanomaterials. The as-exfoliated MoS₂ nanosheets possess superior biomedical stability as nanocarriers to load antibiotic drugs. They show a high photothermal conversion effect and thus induce a synergetic effect of chemotherapy and photothermal therapy to harvest enhanced antibiofilm activity under near-infrared (NIR) light. All these results offer an appealing strategy toward the synthesis and application of ultrathin TMD nanosheets, with great implications for their development.

Systematic Investigation of Two-Dimensional DNA Nanoassemblies for Construction of a Nonspecific Sensor Array

We have performed a systematic study to analyze the effect of ssDNA length, nucleobase composition, and the type of two-dimensional nanoparticles (2D-nps) on the desorption response of 36 two-dimensional nanoassemblies (2D-NAs) against several proteins. The studies were performed using fluorescently labeled polyA, polyC, and polyT with 23, 18, 12, and 7 nucleotide-long sequences. The results suggest that the ssDNAs with polyC and longer sequences are more resistant to desorption, compared to their counterparts. In addition, 2D-NAs assembled using WS₂ were least susceptible to desorption by the proteins tested, whereas nGO 2D-NAs were the most susceptible nanoassemblies. Later, the results of these systematic studies were used to construct a sensor array for discrimination of seven model proteins (BSA, lipase, alkaline phosphatase, acid phosphatase, protease, β-galactosidase, and Cytochrome c). Neither the ssDNAs nor the 2D-nps have any specific interaction with the proteins tested. Only the displacement of the ssDNAs from the 2D-np surface was measured upon the disruption of the existing forces within 2D-NAs. A customized sensor array with five 2D-NAs was developed as a result of a careful screening/filtering process. The sensor array was tested against 200 nM of protein targets, and each protein was discriminated successfully. The results suggest that the systematic studies performed using various ssDNAs and 2D-nps enabled the construction of a sensor array without a bind-and-release sensing mechanism. The studies also demonstrate the significance of systematic investigations in the construction of two-dimensional DNA nanoassemblies for functional studies.

Antimicrobial peptide based magnetic recognition elements and Au@Ag-GO SERS tags with stable internal standards: a three in one biosensor for isolation, discrimination and killing of multiple bacteria in whole blood

A SERS based biosensor has been developed for isolation, detection and killing of multiple bacterial pathogens.

In this study, a new biosensor based on a sandwich structure has been developed for the isolation and detection of multiple bacterial pathogens via magnetic separation and SERS tags. This novel assay relies on antimicrobial peptide (AMP) functionalized magnetic nanoparticles as “capturing” probes for bacteria isolation and gold coated silver decorated graphene oxide (Au@Ag-GO) nanocomposites modified with 4-mercaptophenylboronic acid (4-MPBA) as SERS tags. When different kinds of bacterial pathogens are combined with the SERS tags, the “fingerprints” of 4-MPBA show corresponding changes due to the recognition interaction between 4-MPBA and different kinds of bacterial cell wall. Compared with the label-free SERS detection of bacteria, 4-MPBA here can be used as an internal standard (IS) to correct the SERS intensities with high reproducibility, as well as a Raman signal reporter to enhance the sensitivity and amplify the differences among the bacterial “fingerprints”. Thus, three bacterial pathogens (Escherichia coli, Staphylococcus aureus and Pseudomonas aeruginosa) were successfully isolated and detected, with the lowest concentration for each of the strains detected at just 10¹ colony forming units per mL (CFU mL^–1). According to the changes in the “fingerprints” of 4-MPBA, three bacterial strains were successfully discriminated using discriminant analysis (DA). In addition, the AMP modified Fe₃O₄NPs feature high antibacterial activities, and can act as antibacterial agents with low cellular toxicology in the long-term storage of blood for future safe blood transfusion applications. More importantly, this novel method can be applied in the detection of bacteria from clinical patients who are infected with bacteria. In the validation analysis, 97.3% of the real blood samples (39 patients) could be classified effectively (only one patient infected with E. coli was misclassified). The multifunctional biosensor presented here allows for the simultaneous isolation, discrimination and killing of bacteria, suggesting its high potential for clinical diagnosis and safe blood transfusions.

An array consisting of glycosylated quantum dots conjugated to MoS2 nanosheets for fluorometric identification and quantitation of lectins and bacteria

A fluorescent array based on the use of saccharide-functionalized multicolored quantum dots (s-QDs) and of 4-mercaptophenylboronic acid-functionalized MoS₂ nanosheets (PBA-MoS₂) was constructed for multiple identification and quantitation of lectins and bacteria. In this array, the fluorescence of the s-QDs is quenched by the PBA-MoS₂ nanosheets. In the presence of multiple lectins, s-QDs differentially detach from the surface of PBA-MoS₂ nanosheets, producing distinct fluorescence response patterns due to both quenching and enhancement of fluorescence. By analyzing the fluorescence responses with linear discriminant analysis, multiple lectins and bacteria were accurately identified with 100% accuracy. The limits of detection of Concanavalin A, Pisum sativum agglutinin, Peanut agglutinin, and Ricius communis I agglutinin are as low as 3.7, 8.3, 4.2 and 3.9 nM, respectively. The array has further been evidenced to be potent for distinguishing and quantifying different bacterial species by recognizing their surface lectins. The detection limits of Escherichia coli and Enterococcus faecium are 87 and 66 cfu mL^-1, respectively. Graphical abstract Schematic of a fluorometric array based on the use of saccharides-functionalized quantum dots (s-QDs) and 4-mercaptophenylboronic acid-functionalized MoS₂ (PBA- MoS₂) nanosheets. This array was successfully applied to simultaneously analysis of lectins, bacteria in real samples with high sensitivity and accuracy.

Design of DNA-based innovative computing system of digital comparison

Despite great potential and extensive interest in developing biomolecule-based computing, the development of even basic molecular logic gates is still in its infancy. Digital comparator (DC) is the basic unit in traditional electronic computers, but it is difficult to construct a system for achieving large-scale integration. Here, we construct, for the first time, a novel logic computing system of DCs that can compare whether two or more numbers are equal. Our approach is by taking advantage of facile preparation and unique properties of graphene oxide and DNA. The DC system reported in this work is developed by the DNA hybridization and effective combination of GO and single-stranded DNA, which is regarded as the reacting platform. On the basis of this platform and reaction principle, we have developed 2-inputs, 3-inputs, and 4-inputs DCs to realize the comparison of two or more binary numbers. We predict that such a state-of-the-art logic system enables its functionality with large-scale input signals, providing a new direction toward prototypical DNA-based logic operations and promoting the development of advanced logic computing. STATEMENT OF SIGNIFICANCE: The overarching objective of this paper is to explore the construction of a novel DNA computing system of digital comparator driven by the interaction of DNA and graphene oxide (GO). GO can efficient bind the dye-labeled, single-stranded DNA probe and then quench its fluorescence. In the case of the target appearing, specific binding between the single-stranded probe and its target occurs, changing the conformation and relationship with GO, then restoring the fluorescence of the dye. We have developed the 2-inputs, 3-inputs, and 4-inputs digital comparator circuits, which are expected to realize the comparison of large-scale input signals and can avoid the problems of design complexity and manufacturing cost of integrated circuits in traditional computing.