Protein Sensing and Cell Discrimination Using a Sensor Array Based on Nanomaterial-Assisted Chemiluminescence

Machine learning assisted discrimination and detection of antibiotics by using multicolor microfluidic chemiluminescence detection chip

The fabrication of multicolor chemiluminescence (CL) sensing chip for the discrimination and detection of multianalytes remains a great challenge. Herein, machine learning assisted multicolor microfluidic CL detection chip for the identification and concentration prediction of antibiotics was presented. Firstly, a three-channel microfluidic CL detection chip was fabricated. The three detection zones of the microfluidic detection chip were modified with CL catalyst Co(II) and different CL reagents including luminol, luminol mixed with fluorescein, and luminol mixed with phloxine B, respectively. Strong blue, green and pink-purple colored light emissions can be generated from the three detection zones in the presence of H2O2 solution. The three multicolor CL emissions show different degrees of reduce in intensity and change in color in the presence of different antibiotics, including diethylstilbestro (DES), metronidazole (MNZ), kanamycin (KAN), isoniazide (INH), and ceftiofur sodium (CS), resulting in distinct fingerprint-like response patterns. The red (R), green (G), blue (B) and gray scale values of the three multicolor light emissions were extracted and ten characteristic sensing parameters were chosen to obtain multicolor CL response database. Then, machine learning assisted data analysis were carried out. The five antibiotics can be facilely classified by using principal component analysis (PCA) and hierarchical clustering analysis (HCA), and further quantified by using deep neural networks (DNN) algorithm. Good results were obtained for identification of binary antibiotic mixtures, spiked antibiotics in water samples, and unknown antibiotic samples. Satisfied results were obtained for concentration prediction of antibiotics. This work provides a simple machine learning assisted and multicolor microfluidic CL detection chip based CL sensing strategy for discrimination and quantitative detection of multiple analytes.

Peptomer substrates for quantitative pattern-recognition sensing of proteases

The utility of active proteases as biomarkers is often limited by overlapping substrate specificity. Here, this feature is leveraged to develop a quantitative pattern-recognition sensing system driven by the degradation patterns of peptide-peptoid hybrid substrates to classify proteases and estimate their concentration by multivariate data analysis.

Portable and Label-Free Sensor Array for Discriminating Multiple Analytes via a Handheld Gas Pressure Meter

Cross-reactive sensor arrays are useful for discriminating multiple analytes in a complex sample. Herein, a portable and label-free gas pressure sensor array was proposed for multiplex analysis via a handheld gas pressure meter. It is based on the interaction diversity of analytes with catalase-like nanomaterials, including Pt nanoparticles (PtNP), Co₃O₄ nanosheets (Co₃O₄NS), and Pt-Co alloy nanosheets (PtCoNS), respectively. Thus, the diverse influence of analytes on the catalase-like activity could be output as the difference in the gas pressure. By using principal component analysis, eight proteins were well distinguished by the gas pressure sensor array at the 10 nM level within 12 min. Moreover, different concentrations of proteins and mixtures of proteins could likewise be discriminated. More importantly, the effective discrimination of proteins in human serum and discrimination of five kinds of cells further confirmed the potential of the gas pressure sensor array. Therefore, it provides a portable, cheap, sensitive, and label-free gas pressure sensor array, which is totally different from the reported sensor arrays and holds great potential for portable and cheap discrimination of multiple analytes.

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.

Evolution of Supramolecular Systems Towards Next-Generation Biosensors

Supramolecular materials, which rely on dynamic non-covalent interactions, present a promising approach to advance the capabilities of currently available biosensors. The weak interactions between supramolecular monomers allow for adaptivity and responsiveness of supramolecular or self-assembling systems to external stimuli. In many cases, these characteristics improve the performance of recognition units, reporters, or signal transducers of biosensors. The facile methods for preparing supramolecular materials also allow for straightforward ways to combine them with other functional materials and create multicomponent sensors. To date, biosensors with supramolecular components are capable of not only detecting target analytes based on known ligand affinity or specific host-guest interactions, but can also be used for more complex structural detection such as chiral sensing. In this Review, we discuss the advancements in the area of biosensors, with a particular highlight on the designs of supramolecular materials employed in analytical applications over the years. We will first describe how different types of supramolecular components are currently used as recognition or reporter units for biosensors. The working mechanisms of detection and signal transduction by supramolecular systems will be presented, as well as the important hierarchical characteristics from the monomers to assemblies that contribute to selectivity and sensitivity. We will then examine how supramolecular materials are currently integrated in different types of biosensing platforms. Emerging trends and perspectives will be outlined, specifically for exploring new design and platforms that may bring supramolecular sensors a step closer towards practical use for multiplexed or differential sensing, higher throughput operations, real-time monitoring, reporting of biological function, as well as for environmental studies.

A chemiluminescence sensor array for discrimination of seven toxicants

A chemiluminescence (CL) sensor array was developed based on 11 CL systems cross-combined by three luminescence reagents and four oxidants. Using the CL sensor array, we measured seven toxicants, including morphine, ketamine, diazepam, chlorpromazine, strychnine, paraquat, and fenpropathrin, which represent psychotropic drugs, sedatives and hypnotics, rodenticides, herbicides, and insecticides, respectively. The CL response pattern or 'fingerprints' were obtained for a given compound on the sensor array and then discriminated through principal component analysis. The established sensor array has been applied to real-life samples and the results showed that it possesses excellent discrimination.

Providing Multicolor Plasmonic Patterns with Au@Ag Core-Shell Nanostructures for Visual Discrimination of Biogenic Amines

Biogenic amines (BAs) are known as substantial indicators of the quality and safety of food. Developing rapid and visual detection methods capable of simultaneously monitoring BAs is highly desired due to their harmful effects on human health. In the present study, we have designed a multicolor sensor array consisting of two types of gold nanostructures (i.e., gold nanorods (AuNRs) and gold nanospheres (AuNSs)) for the discrimination and determination of critical BAs (i.e., spermine (SM), tryptamine (TT), ethylenediamine (EA), tyramine (TR), spermidine (SD), and histamine (HT)). The design principle of the probe was based on the metallization of silver ions on the surface of AuNRs and AuNSs in the presence of BAs, forming Au@Ag core-shell nanoparticles. Changes in the surface composition, size, and aspect ratio of AuNSs and AuNRs induced a blue shift in the plasmonic band, which was accompanied by sharp and rainbowlike color variations in the solution. The collected data were visually assessed and statistically analyzed by various data visualization and pattern recognition methods. Namely, linear discriminant analysis (LDA) and partial least squares (PLS) regression were employed for the qualitative and quantitative determination of BAs. The responses were linearly correlated to the concentrations of BAs in a wide range of 10-800, 20-800, 40-800, 40-800, 60-800, and 80-800 μmol L^-1 with the limit of detections of 2.46, 4.79, 8.58, 14.26, 10.03, and 27.29 μmol L^-1 for SD, SM, TT, HT, EA, and TR, respectively. Finally, the practical applicability of the sensor array was investigated by the determination of BAs in meat and fish samples by which the potential of the probe for on-site determination of food freshness/spoilage was successfully verified.

Integral Multielement Signals by DNA-Programmed UCNP-AuNP Nanosatellite Assemblies for Ultrasensitive ICP-MS Detection of Exosomal Proteins and Cancer Identification

Exosomes are expected to be used as cancer biomarkers because they carry a variety of cancer-related proteins inherited from parental cells. However, it is still challenging to develop a sensitive, robust, and high-throughput technique for simultaneous detection of exosomal proteins. Herein, three aptamers specific to cancer-associated proteins (CD63, EpCAM, and HER2) are selected to connect gold nanoparticles (AuNPs) as core with three different elements (Y, Eu, and Tb) doped up-conversion nanoparticles (UCNPs) as satellites, thereby forming three nanosatellite assemblies. The presence of exosomes causes specific aptamers to recognize surface proteins and release the corresponding UCNPs, which can be simultaneously detected by inductively coupled plasma-mass spectrometry (ICP-MS). It is worth noting that rare earth elements are scarcely present in living systems, which minimize the background for ICP-MS detection and exclude potential interferences from the coexisting species. Using this method, we are able to simultaneously detect three exosomal proteins within 40 min, and the limit of detection for exosome is 4.7 × 10³ particles/mL. The exosomes from seven different cell lines (L-02, HepG2, GES-1, MGC803, AGS, HeLa, and MCF-7) can be distinguished with 100% accuracy by linear discriminant analysis. In addition, this analytical strategy is successfully used to detect exosomes in clinical samples to distinguish stomach cancer patients from healthy individuals. These results suggest that this sensitive and high-throughput analytical strategy based on ICP-MS has the potential to play an important role in the detection of multiple exosomal proteins and the identification of early cancer.

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.

Mitochondria-Targeted Sensor Array with Aggregation-Induced Emission Luminogens for Identification of Various Cells

Accurate discrimination of cancerous cells is a good solution for early diagnosis of tumors. The mitochondrion plays an important role in cells. Herein, the five aggregation-induced emission luminogens (AIEgens) with various double positive charges are synthesized to image mitochondria. Tetraphenylethylene (TPE) molecules are modified by methoxy groups, conjugated donor-acceptor, and different positive charges to achieve multicolor emission. The five AIEgens form the PTx-Sa (positive mitochondria-target molecular sensor array) to perform cross-fluorescence response based on the mitochondria-targeted imaging to achieve the discrimination of various cells. Principal component analysis of the cross-response fluorescence data of PTx-Sa shows that 100% accurate identification of various cells, including cancer cells and normal cells, digestive tract cancer cells, gastric cancer cells, and mixed gastric cancer cells. By support vector machine to show the predictive ability of PTx-Sa to unknown cells by using blind samples. This is the first time to apply mitochondria-targeted sensor array to identification of various cells.

Protein Discrimination Using a Fluorescence-Based Sensor Array of Thiacarbocyanine-GUMBOS

Sensitive and selective detection of proteins from complex samples has gained substantial interest within the scientific community. Early and precise detection of key proteins plays an important role in potential clinical diagnosis, treatment of different diseases, and proteomic research. In the study reported here, six different compounds belonging to a group of uniform materials based on organic salts (GUMBOS) have been synthesized using three thiacarbocyanine (TC) dyes and employed as fluorescent sensors. Fluorescence properties of micro- and nanoaggregates of these TC-based GUMBOS formed in phosphate buffer solutions are studied in the absence and presence of seven proteins. Fluorescence response patterns of these TC-based GUMBOS were analyzed by linear discriminant analysis (LDA). The constructed LDA model allowed discrimination of these seven proteins at various concentrations with 100% accuracy. The sensing and discrimination abilities of these TC-based GUMBOS were further evaluated in mixtures of two major proteins, i.e., human serum albumin and hemoglobin. Fluorescence response patterns of these mixtures were analyzed by LDA. This model allowed discrimination of various mixtures with 100% accuracy. Moreover, spiked urine samples were prepared and the responses of these sensors were collected and analyzed by LDA. Remarkably, discrimination of these seven proteins was also achieved with 100% accuracy.

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.

Efficient Cascade Resonance Energy Transfer in Dynamic Nanoassembly for Intensive and Long-Lasting Multicolor Chemiluminescence

Light emission induced by chemical reactions, known as chemiluminescence (CL), has been widely used for bioassays, biosensors, imaging, and illumination applications. Most known CL systems exhibit flash-type single-color light emissions, which limit their applications. Long-lasting multicolor CL in aqueous solutions is highly desirable, especially for biological applications, but remains a challenge. Herein, we report a simple strategy of achieving highly efficient cascade Förster resonance energy transfer (FRET) in the dynamic nanoassembly of β-cyclodextrin (β-CD), CL reagents, and fluorophores in aqueous solution, which emits intensive multicolor CL with adjustable wavelength within 410-610 nm. β-CD can bind CL reagents and fluorophores to form a dynamic nanoassembly. These nanoassemblies can bring the included luminescent intermediate and fluorophores into close proximity and proper alignment, which should greatly enhance the FRET efficiency between luminescent intermediate and fluorophores. Indeed, the cascade FRET efficiency in this supramolecular nanoassembly reaches up to 92%, which is comparable with the cascade FRET systems based on covalently linked donors and acceptors. By using hydroxypropyl methylcellulose as the thickener to slow the diffusion (to elongate the CL emission), and using Ca(OH)₂ solid (a low solubility strong base) as buffer to maintain the pH in the optimal range for the CL reaction, this nanoassembly system has been further developed to achieve slow-diffusion-controlled catalytic CL reactions, which enables long-lasting multicolor CL in aqueous solution that is visible to naked eyes and lasts for more than 20 h. The multicolor CL systems can be used to prepare transformable two-dimensional multicolor codes for encryption application.

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.

Synthesis of Nano-Praseodymium Oxide for Cataluminescence Sensing of Acetophenone in Exhaled Breath

In this work, we successfully developed a novel and sensitive gas sensor for the determination of trace acetophenone based on its cataluminescence (CTL) emission on the surface of nano-praseodymium oxide (nano-Pr₆O₁₁). The effects of working conditions such as temperature, flow rate, and detecting wavelength on the CTL sensing were investigated in detail. Under the optimized conditions, the sensor exhibited linear response to the acetophenone in the range of 15-280 mg/m³ (2.8-52 ppm), with a correlation coefficient (R²) of 0.9968 and a limit of detection (S/N = 3) of 4 mg/m³ (0.7 ppm). The selectivity of the sensor was also investigated, no or weak response to other compounds, such as alcohols (methanol, ethanol, n-propanol, iso-propanol, n-butanol), aldehyde (formaldehyde and acetaldehyde), benzenes (toluene, o-xylene, m-xylene, p-xylene), n-pentane, ethyl acetate, ammonia, carbon monoxide, carbon dioxide. Finally, the present sensor was applied to the determination of acetophenone in human exhaled breath samples. The results showed that the sensor has promising application in clinical breath analysis.

Sensitive discrimination of glycoproteins and cell differentiation with an array sensing platform exploiting pyrene-derived amphiphile/surfactant assemblies

An array sensing platform exploiting phenyl boronic acid-functionalized pyrene amphiphile/surfactant assemblies is constructed for glycoprotein discrimination, achieving a discrimination sensitivity of 50 nM. Gastric cancer cell lines of various differentiation grades are successfully discriminated, demonstrating its great potential in sensitive differentiation of glycoprotein-related samples in biomedical diagnosis.

Discrimination of proteins through interaction with pyrene-labelled polymer aggregates

A pyrene-labelled PDMAEMA (2-(dimethylamino)ethyl methacrylate) polymer was synthesized through a controlled radical RAFT polymerisation approach. An average pyrene content of 3.65% was determined by UV/Vis and ¹H NMR measurements. DLS measurements reveal the formation of polymer aggregates with an average size of 172 nm in aqueous phosphate buffer indicating the presence of hydrophobic interactions between pyrene and/or DMAEMA moieties of adjacent polymer chains. Furthermore, this aggregation results in the appearance of two characteristic emission bands at 394 and 488 nm analyzed by fluorescence measurements. Based on spectral changes of the so-called monomer and excimer emission intensity, the specific discrimination of various non-metallo- and metallo proteins was realized using an optical fingerprint approach. DLS and fluorescence measurements show a significant dependence of the structural characteristics of the analytes on the presence of different binding modes between the hydrophilic DMAEMA side groups of the polymer and the proteins, resulting in a molecular disassembly of the aggregates and/or fluorescence quenching. Furthermore, pH, temperature and ionic strength dependence of the sensor polymer with BSA was investigated to optimise the external parameters. Based on these results, the most specific discrimination of the analyzed proteins was obtained using a sodium chloride concentration of 50 mM and a pH of 7.0. This study gives fundamental insights into the sensing performance of a novel one-component pyrene-based polymer system and its application as a protein sensor.

Cataluminescence sensor for highly sensitive and selective detection of iso-butanol

In this paper, a gaseous sensor was described for detection of iso-butanol on the basis of its strong cataluminescence (CTL) emission on nano-MgO surface. The sensor showed high sensitivity and specificity to iso-butanol with response time less than 1 s and recovery time less than 18 s. A good linearly relationship between CTL intensity and the concentration of iso-butanol was observed in the range of 7.6-3350 mg/m³ (r = 0.9992), the limit of detection was 2.5 mg/m³. The proposed CTL sensor exhibits good specificity to iso-butanol against other compounds including common alcohols. The possible reaction paths of iso-butanol on the MgO surface were investigated in detail. Results shows that the hydrogen atom abstraction of iso-butanol to form β-R_iso following consumption via Waddington mechanism possible is a major reaction channel for CTL emission. The sensor was applied to analyze iso-butanol in spiked samples, satisfactory recoveries were obtained in the range of 96.6-112.8% and the RSDs were 5.0-10.1%, indicating that the proposed sensor is a promising candidate for rapid analysis of iso-butanol.

Gold Nanorod-Based Chrono-Colorimetric Sensor Arrays: A Promising Platform for Chemical Discrimination Applications

Most array-based sensing platforms, to date, utilize static response patterns for discrimination of a wide variety of analytes, but only a few studies have focused on the important task of quantitatively resolving structural isomers, which are nowadays important because of their broad usage in medicines and industries. A possible way of accomplishing this feat is to combine kinetic (rather than static) sensor response profiles with the chemical tongue strategy to allow the development of array-based sensors for isomeric discrimination. Here, by adding the time dimension, a simple and novel gold nanorod (AuNR)-based chrono-colorimetric sensor array is proposed for chemical discrimination applications. Because of their similar structure but different redox potentials, dihydroxybenzene (DHB) structural isomers have been chosen, as models, to evaluate the applicability of the proposed array. The principle of the array relies on various growth rates of silver shells on AuNRs at different silver ion/AuNR concentration ratios owing to the different kinetic behaviors of DHBs, which can be used as fingerprints to identify DHBs with the help of multivariate analysis methods. The combinatorial colorimetric response of AuNRs upon DHB addition has been analyzed by linear discriminant analysis and hierarchical cluster analysis. Finally, identification of individual DHBs or their mixtures in real samples confirms the potential application of the proposed array.

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.

Carbon Nanodots-Based Fluorescent Turn-On Sensor Array for Biothiols

Biothiols play important roles in biological processes. In this study, a novel sensor array-based method was proposed to detect and differentiate biothiols. The sensor array was constructed using three kinds of Ag⁺-sensitive carbon nanodots (CDs). The CDs were synthesized with amino acids and urea as carbon sources via a simple microwave method. Results revealed that Ag⁺ can bind with CDs and depress the fluorescence of CDs, while the subsequently joined biothiols can take Ag⁺ away from CDs and recover the fluorescence of CDs. Due to the different binding ability between Ag⁺ and various CDs, as well as Ag⁺ and various biothiols, the CD-Ag⁺ array exhibits a unique pattern of fluorescence variations when interacting with six biothiol samples (cysteamine, dithiothreitol, mercaptosuccinic acid, glutathione, mercaptoacetic acid, and mercaptoethanol). Principal component analysis (PCA) was applied to analyze the pattern and generate a clustering map for a clearer identification of these biothiols. PCA can also be employed to simplify the established three-sensor array into a two-sensor array. Both the three- and two-sensor arrays can identify these biothiols in a wide biothiol concentration range (>10 μM).

Functionalized Ionic Microgel Sensor Array for Colorimetric Detection and Discrimination of Metal Ions

A functional ionic microgel sensor array was developed by using 1-(2-pyridinylazo)-2-naphthaleno (PAN)- and bromothymol blue (BTB)-functionalized ionic microgels, which were designed and synthesized by quaternization reaction and anion-exchange reaction, respectively. The PAN microgels (PAN-MG) and BTB microgels (BTB-MG) were spherical in shape with a narrow size distribution and exhibited characteristic colors in aqueous solution in the presence of various trace-metal ions, which could be visually distinguished by the naked eye. Such microgels could be used for the colorimetric detection of various metal ions in aqueous solution at submicromolar levels, which were lower than the U.S. Environmental Protection Agency standard for the safety limit of metal ions in drinking water. A total of 10 species of metal ions in aqueous solution, Ba²⁺, Cr³⁺, Mn²⁺, Pb²⁺, Fe³⁺, Co²⁺, Zn²⁺, Ni²⁺, Cu²⁺, and Al³⁺, were successfully discriminated by the as-constructed microgel sensor array combined with discriminant analysis, agglomerative hierarchical clustering, and leave-one-out cross-validation analysis.

Cancer Cell Discrimination Using Host-Guest "Doubled" Arrays

We report a nanosensor that uses cell lysates to rapidly profile the tumorigenicity of cancer cells. This sensing platform uses host-guest interactions between cucurbit[7]uril and the cationic headgroup of a gold nanoparticle to non-covalently modify the binding of three fluorescent proteins of a multi-channel sensor in situ. This approach doubles the number of output channels to six, providing single-well identification of cell lysates with 100% accuracy. Significantly, this classification could be extended beyond the training set, determining the invasiveness of novel cell lines. The unique fingerprint of these cell lysates required minimal sample quantity (200 ng, ∼1000 cells), making the methodology compatible with microbiopsy technology.

Recent advances in cataluminescence-based optical sensing systems

Recent advances in the development of cataluminescence focused on oxygen, temperature, catalyst and instrumentation are summarized.

Cobalt(ii)-8-hydroxyquinoline-5-sulfonic acid complex/N-(4-aminobutyl)-N-ethylisoluminol/reduced graphene hybrids as nanocatalytic reaction platforms for chemiluminescence

The as-prepared Co^II(HQS)₂/ABEI/rGO hybrids exhibited excellent CL activity when reacted with hydrogen peroxide, the dissolved oxygen and periodate in alkaline solution.

Discrimination of Metalloproteins by a Mini Sensor Array Based on Bispyrene Fluorophore/Surfactant Aggregate Ensembles

Fluorescent sensor arrays with pattern recognition ability have been widely used to detect and identify multiple chemically similar analytes. In the present work, two particular bispyrene fluorophores containing hydrophilic oligo(oxyethylene) spacer, 6 and 4, were synthesized, but one is with and the other is without cholesterol unit. Their ensembles with cationic surfactant (CTAB) assemblies realize multiple fluorescence responses to different metalloproteins, including hemoglobin, myoglobin, ferritin, cytochrome c, and alcohol dehydrogenase. The combination of fluorescence variation at monomer and excimer emission of the two binary sensor ensembles enables the mini sensor array to provide a specific fingerprint pattern to each metalloprotein. Linear discriminant analysis shows that the two-ensemble-sensor-based array could well discriminate the five tested metalloproteins. The present work realizes using a mini sensor array to accomplish discrimination of complex analytes like proteins. They also display a very high sensitivity to the tested metalloproteins with detection limits in the range of picomolar concentration.

Pattern-based sensing of triple negative breast cancer cells with dual-ligand cofunctionalized gold nanoclusters

Early detection of breast cancer is a critical component in patient prognosis and establishing effective therapy regimens. Here, we developed an easily accessible yet potentially powerful sensor to detect cancer cell targets by utilizing seven dual-ligand cofunctionalized gold nanoclusters (AuNCs) as both effective cell recognition elements and signal transducers. On the basis of this AuNC multichannel sensor, we have successfully distinguished healthy, cancerous and metastatic human breast cells with excellent reproducibility and high sensitivity. Triple negative breast cancer cells (TNBCs), which exhibit low expression of the estrogen receptor, progesterone receptor, and human epidermal growth factor receptor-2, were identified. The high accuracy of the blind breast cell sample tests further validates the practical application of the sensor array. In addition, the versatility of the sensor array is further justified by identifying amongst distinct cell types, different cell concentrations and cell mixtures. Notably, the drug-resistant cancer cells can also be efficiently discriminated. Furthermore, the dual-ligand cofunctionalized AuNCs can efficiently differentiate different cells from the peripheral blood of tumor-free and tumor-bearing mice. Taken together, this fluorescent AuNCs based array provides a powerful cell analysis tool with potential applications in biomedical diagnostics.

Design a New Strategy Based on Nanoparticle-Enhanced Chemiluminescence Sensor Array for Biothiols Discrimination

Array-based sensor is an interesting approach that suggests an alternative to expensive analytical methods. In this work, we introduce a novel, simple, and sensitive nanoparticle-based chemiluminescence (CL) sensor array for discrimination of biothiols (e.g., cysteine, glutathione and glutathione disulfide). The proposed CL sensor array is based on the CL efficiencies of four types of enhanced nanoparticle-based CL systems. The intensity of CL was altered to varying degrees upon interaction with biothiols, producing unique CL response patterns. These distinct CL response patterns were collected as “fingerprints” and were then identified through chemometric methods, including linear discriminant analysis (LDA) and hierarchical cluster analysis (HCA). The developed array was able to successfully differentiate between cysteine, glutathione and glutathione disulfide in a wide concentration range. Moreover, it was applied to distinguish among the above analytes in human plasma.

Dual-Functional Nanoparticles for In Situ Sequential Detection and Imaging of ATP and H2 O2

Within a complex biological sample, the in situ sequential detection of multiple molecules without any interference is greatly desirable. Dual-functional nanoparticles are constructed, with the enzyme-based core-shell structures, for the in situ sequential detection of ATP and H2 O2 within the same biological system.

Ratiometric Array of Conjugated Polymers-Fluorescent Protein Provides a Robust Mammalian Cell Sensor

Supramolecular complexes of a family of positively charged conjugated polymers (CPs) and green fluorescent protein (GFP) create a fluorescence resonance energy transfer (FRET)-based ratiometric biosensor array. Selective multivalent interactions of the CPs with mammalian cell surfaces caused differential change in FRET signals, providing a fingerprint signature for each cell type. The resulting fluorescence signatures allowed the identification of 16 different cell types and discrimination between healthy, cancerous, and metastatic cells, with the same genetic background. While the CP-GFP sensor array completely differentiated between the cell types, only partial classification was achieved for the CPs alone, validating the effectiveness of the ratiometric sensor. The utility of the biosensor was further demonstrated in the detection of blinded unknown samples, where 121 of 128 samples were correctly identified. Notably, this selectivity-based sensor stratified diverse cell types in minutes, using only 2000 cells, without requiring specific biomarkers or cell labeling.

Multicolor Quantum Dot-Based Chemical Nose for Rapid and Array-Free Differentiation of Multiple Proteins

Nanomaterial-based differential sensors (e.g., chemical nose) have shown great potential for identification of multiple proteins because of their modulatable recognition and transduction capability but with the limitation of array separation, single-channel read-out, and long incubation time. Here, we develop a multicolor quantum dot (QD)-based multichannel sensing platform for rapid identification of multiple proteins in an array-free format within 1 min. A protein-binding dye of bromophenol blue (BPB) is explored as an efficient reversible quencher of QDs, and the mixture of BPB with multicolor QDs may generate the quenched QD-BPB complexes. The addition of proteins will disrupt the QD-BPB complexes as a result of the competitive protein-BPB binding, inducing the separation of BPB from the QDs and the generation of distinct fluorescence patterns. The multicolor patterns may be collected at a single-wavelength excitation and differentiated by a linear discriminant analysis (LDA). This multichannel sensing platform allows for the discrimination of ten proteins and seven cell lines with the fastest response rate reported to date, holding great promise for rapid and high-throughput medical diagnostics.

A Supramolecular Sensor Array Using Lanthanide-Doped Nanoparticles for Sensitive Detection of Glyphosate and Proteins

Lanthanide (Ln(3+))-doped nanoparticles (NPs) are an intensive area of research in chemical and materials sciences. Herein a sensor array of Ln(3+)-doped NPs was developed for the first time toward sensitive molecular sensing based on a novel strategy of the hybridized time-resolved Förster resonance energy transfer (TR-FRET) with the indicator displacement assay (IDA) concept (TR-FRET-IDA). The sensor platform was generated in situ by binding a series of negatively charged indicators on the surface of ligand-free LiYF4:Ce/Tb NPs. The TR-FRET between NPs and dyes resulted in indicator emission and was employed as a means of removing undesired short-lived background luminescence from the indicator effectively. Displacement of indicators from the NP/indicator ensembles by glyphosate, a common herbicide, led to turn-off of the indicator emission. The sensor array was able to successfully discriminate 11 biologically relevant anions with high accuracy and sensitivity in pure aqueous buffer both qualitatively and quantitatively. Furthermore, the differentiation of six model proteins in the nM range was achieved with 100% accuracy for the classification, thereby demonstrating the versatility of this simple sensor platform. The study of the mechanism of binding and signal modulation further verified TR-FRET-IDA as a reliable sensing paradigm.

A Multichannel Biosensor for Rapid Determination of Cell Surface Glycomic Signatures

Cell surface glycosylation serves a fundamental role in dictating cell and tissue behavior. Cell surface glycomes differ significantly, presenting viable biomarkers for identifying cell types and their states. Glycoprofiling is a challenging task, however, due to the complexity of the constituent glycans. We report here a rapid and effective sensor for surface-based cell differentiation that uses a three-channel sensor produced by noncovalent conjugation of a functionalized gold nanoparticle (AuNP) and fluorescent proteins. Wild-type and glycomutant mammalian cells were effectively stratified using fluorescence signatures obtained from a single sensor element. Blinded unknowns generated from the tested cell types were identified with high accuracy (44 out of 48 samples), validating the robustness of the multichannel sensor. Notably, this selectivity-based high-throughput sensor differentiated between cells, employing a nondestructive protocol that required only a single well of a microplate for detection.

Simple and Sensitive Discrimination of Amino Acids with Functionalized Silver Nanoparticles

A chemiluminescence (CL) sensing method for amino acid discrimination based on luminol functionalized silver nanoparticles (LumAgNPs) has been developed. Luminescence emission in the presence of hydrogen peroxide under neutral conditions was characterized in three ways: the time required for the signal to appear (Ta), the time required to reach maximum luminescence (Tp), and CL intensity. These factors were found to change upon interaction of the nanoparticles with various amino acids, leading to distinct response patterns characteristic of each analyte. Seven amino acids (l-cysteine, l-proline, l-phenylalanine, l-arginine, l-threonine, l-glutamic acid, and l-tyrosine) were identified at a concentration of 10 ng/mL. This sensitivity is about 3 orders of magnitude better than that of recently reported methods based on fluorescent sensor arrays using cucurbit[n]uril and comparable to high-performance liquid chromatography. Application to 27 unknown samples gave a 96.3% success rate at the 10 ng/mL level.

Array-based sensing using nanoparticles: an alternative approach for cancer diagnostics

Array-based sensing using nanoparticles (NPs) provides an attractive alternative to specific biomarker-focused strategies for cancer diagnosis. The physical and chemical properties of NPs provide both the recognition and transduction capabilities required for biosensing. Array-based sensors utilize a combined response from the interactions between sensors and analytes to generate a distinct pattern (fingerprint) for each analyte. These interactions can be the result of either the combination of multiple specific biomarker recognition (specific binding) or multiple selective binding responses, known as chemical nose sensing. The versatility of the latter array-based sensing using NPs can facilitate the development of new personalized diagnostic methodologies in cancer diagnostics, a necessary evolution in the current healthcare system to better provide personalized treatments. This review will describe the basic principle of array-based sensors, along with providing examples of both invasive and noninvasive samples used in cancer diagnosis.

Next-generation sequencing as input for chemometrics in differential sensing routines

Differential sensing (DS) methods traditionally use spatially arrayed receptors and optical signals to create score plots from multivariate data which classify individual analytes or complex mixtures. Herein, a new approach is described, in which nucleic acid sequences and sequence counts are used as the multivariate data without the necessity of a spatial array. To demonstrate this approach to DS, previously selected aptamers, identified from the literature, were used as semi-specific receptors, Next-Gen DNA sequencing was used to generate data, and cell line differentiation was the test-bed application. The study of a principal component analysis loading plot revealed cross-reactivity between the aptamers. The technique generates high-dimensionality score plots, and should be applicable to any mixture of complex and subtly different analytes for which nucleic acid-based receptors exist.