Colorimetric Sensor Array Based on Wulff-Type Boronate Functionalized AgNPs at Various pH for Bacteria Identification

Elevating nanomaterial optical sensor arrays through the integration of advanced machine learning techniques for enhancing visual inspection of food quality and safety

Food quality and safety problems caused by inefficient control in the food chain have significant implications for human health, social stability, and economic progress and optical sensor arrays (OSAs) can effectively address these challenges. This review aims to summarize the recent applications of nanomaterials-based OSA for food quality and safety visual monitoring, including colourimetric sensor array (CSA) and fluorescent sensor array (FSA). First, the fundamental properties of various advanced nanomaterials, mainly including metal nanoparticles (MNPs) and nanoclusters (MNCs), quantum dots (QDs), upconversion nanoparticles (UCNPs), and others, were described. Besides, the diverse machine learning (ML) and deep learning (DL) methods of high-dimensional data obtained from the responses between different sensing elements and analytes were presented. Moreover, the recent and representative applications in pesticide residues, heavy metal ions, bacterial contamination, antioxidants, flavor matters, and food freshness detection were comprehensively summarized. Finally, the challenges and future perspectives for nanomaterials-based OSAs are discussed. It is believed that with the advancements in artificial intelligence (AI) techniques and integrated technology, nanomaterials-based OSAs are expected to be an intelligent, effective, and rapid tool for food quality assessment and safety control.

Surface-mediated fluorescent sensor array for identification of gut microbiota and monitoring of colorectal cancer

The development of efficient, accurate, and high-throughput technology for gut microbiota sensing holds great promise in the maintenance of health and the treatment of diseases. Herein, we developed a rapid fluorescent sensor array based on surface-engineered silver nanoparticles (AgNPs) and vancomycin-modified gold nanoclusters (AuNCs@Van) for gut microbiota sensing. By controlling the surface of AgNPs, the recognition ability of the sensor can be effectively improved. The sensor array was used to successfully discriminate six gut-derived bacteria, including probiotics, neutral, and pathogenic bacteria and even their mixtures. Significantly, the sensing system has also been successfully applied to classify healthy individuals and colorectal cancer (CRC) patients rapidly and accurately within 30 min, demonstrating its clinically relevant specificity.

Ensuring food safety by artificial intelligence-enhanced nanosensor arrays

Current analytical methods utilized for food safety inspection requires improvement in terms of their cost-efficiency, speed of detection, and ease of use. Sensor array technology has emerged as a food safety assessment method that applies multiple cross-reactive sensors to identify specific targets via pattern recognition. When the sensor arrays are fabricated with nanomaterials, the binding affinity of analytes to the sensors and the response of sensor arrays can be remarkably enhanced, thereby making the detection process more rapid, sensitive, and accurate. Data analysis is vital in converting the signals from sensor arrays into meaningful information regarding the analytes. As the sensor arrays can generate complex, high-dimensional data in response to analytes, they require the use of machine learning algorithms to reduce the dimensionality of the data to gain more reliable outcomes. Moreover, the advances in handheld smart devices have made it easier to read and analyze the sensor array signals, with the advantages of convenience, portability, and efficiency. While facing some challenges, the integration of artificial intelligence with nanosensor arrays holds promise for enhancing food safety monitoring.

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.

Surveillance of pathogenic bacteria on a food matrix using machine-learning-enabled paper chromogenic arrays

Global food systems can benefit significantly from continuous monitoring of microbial food safety, a task for which tedious operations, destructive sampling, and the inability to monitor multiple pathogens remain challenging. This study reports significant improvements to a paper chromogenic array sensor - machine learning (PCA-ML) methodology sensing concentrations of volatile organic compounds (VOCs) emitted on a species-specific basis by pathogens by streamlining dye selection, sensor fabrication, database construction, and machine learning and validation. This approach enables noncontact, time-dependent, simultaneous monitoring of multiple pathogens (Listeria monocytogenes, Salmonella, and E. coli O157:H7) at levels as low as 1 log CFU/g with over 90% accuracy. The report provides theoretical and practical frameworks demonstrating that chromogenic response, including limits of detection, depends on time integrals of VOC concentrations. The paper also discusses the potential for implementing PCA-ML in the food supply chain for different food matrices and pathogens, with species- and strain-specific identification.

Electrospun cellulose nanofibers immobilized with anthocyanin extract for colorimetric determination of bacteria

A novel smart biochromic textile sensor was developed by immobilizing anthocyanin extract into electrospun cellulose acetate nanofibers to detect bacteria for numerous potential uses, such as healthcare monitoring. Red-cabbage was employed to extract anthocyanin, which was then applied to cellulose acetate nanofibers treated with potassium aluminum sulfate as a mordant. Thus, nanoparticles (NPs) of mordant/anthocyanin (65-115 nm) were generated in situ on the surface of cellulose acetate nanofibrous film. The pH of a growing bacterial culture medium is known to change when bacteria multiply. The absorbance spectra revealed a bluish shift from 595 nm (purple) to 448 nm (green) during the growth of Gram-negative bacteria (E. coli) owing to the discharge of total volatile basic amines as secretion metabolites. On the other hand, the absorption spectra of a growing bacterial culture containing Gram-positive bacteria (L. acidophilus) showed a blue shift from 595 nm (purplish) to 478 nm (pink) as a result of releasing lactic acid as a secretion metabolite. Both absorbance spectra and CIE Lab parameters were used to determine the color shifts. Various analytical techniques were utilized to study the morphology of the anthocyanin-encapsulated electrospun cellulose nanofibers. The cytotoxic effects of the colored cellulose acetate nanofibers were tested.

Antimicrobial Agent Functional Gold Nanocluster-Mediated Multichannel Sensor Array for Bacteria Sensing

Urinary tract infections (UTIs) have greatly affected human health in recent years. Accurate and rapid diagnosis of UTIs can enable a more effective treatment. Herein, we developed a multichannel sensor array for efficient identification of bacteria based on three antimicrobial agents (vancomycin, lysozyme, and bacitracin) functional gold nanoclusters (AuNCs). In this sensor, the fluorescence intensity of the three AuNCs was quenched to varying degrees by the bacterial species, providing a unique fingerprint for different bacteria. With this sensing platform, seven pathogenic bacteria, different concentrations of the same bacteria, and even bacterial mixtures were successfully differentiated. Furthermore, UTIs can be accurately identified with our sensors in ∼30 min with 100% classification accuracy. The proposed sensing systems offer a rapid, high-throughput, and reliable sensing platform for the diagnosis of UTIs.

A review on machine learning-powered fluorescent and colorimetric sensor arrays for bacteria identification

Biosensors have been widely used for bacteria determination with great success. However, the "lock-and-key" methodology used by biosensors to identify bacteria has a significant limitation: it can only detect one species of bacteria. In recent years, optical (fluorescent and colorimetric) sensor arrays are gradually gaining attention from researchers as a new type of biosensor. They can acquire multiple features of a target simultaneously, form a feature pattern, and determine the bacteria species with the help of pattern recognition/machine learning algorithms. Previous reviews in this area have focused on the interaction between the sensor array and bacteria or the materials used to make the sensors. This review, on the other hand, will provide researchers with a better understanding of the field by discussing fluorescent and colorimetric sensor arrays based on the mechanism of optical signal generation. These sensor arrays will be compared based on the identified species. Finally, we will discuss the limitations of these sensor arrays and explore possible solutions.

Biosensors with Boronic Acid-Based Materials as the Recognition Elements and Signal Labels

It is of great importance to have sensitive and accurate detection of cis-diol-containing biologically related substances because of their important functions in the research fields of metabolomics, glycomics, and proteomics. Boronic acids can specifically and reversibly interact with 1,2- or 1,3-diols to form five or six cyclic esters. Based on this unique property, boronic acid-based materials have been used as synthetic receptors for the specific recognition and detection of cis-diol-containing species. This review critically summarizes the recent advances with boronic acid-based materials as recognition elements and signal labels for the detection of cis-diol-containing biological species, including ribonucleic acids, glycans, glycoproteins, bacteria, exosomes, and tumor cells. We also address the challenges and future perspectives for developing versatile boronic acid-based materials with various promising applications.

Detection and discrimination of pathogenic bacteria with nanomaterials-based optical biosensors: A review

Pathogenic bacteria can pose a great threat to food safety and human health. It is therefore imperative to develop a rapid, portable, and sensitive determination and discrimination method for pathogenic bacteria. Over the past few years, various nanomaterials (NMs) have been employed as desirable nanoprobes because they possess extraordinary properties that can be used for optical signal enabled detection and identification of bacteria. By means of modification, NMs can, depending on different mechanisms, sense targets directly or indirectly, which then provides an essential support for the detection and differentiation of pathogenic bacteria. In this review, recent application of NMs-based optical biosensors for food safety bacterial detection and discrimination is performed, mainly in but not limited to noble metal NMs, fluorescent NMs, and point-of-care testing (POCT). This review also focuses on future trends in bacterial detection and discrimination, and machine learning in performing intelligent rapid detection and multiple accurate identification of bacteria.

Identification of Proteins Using Supramolecular Gold Nanoparticle-Dye Sensor Arrays

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

Dual enzyme induced colorimetric sensor for simultaneous identifying multiple pathogens

Rapid and accurate identification of foodborne pathogens improves public health. Currently employed methods are time-consuming, sensitive to environmental factors, and complex. This study develops a colorimetric sensor for detecting multiple bacteria with one probe using double-enzyme-induced colorimetry. Based on alkaline phosphatase (ALP) in bacteria decomposes L-ascorbic acid 2-magnesium phosphate salt hydrate into ascorbic acid (AA). Manganese dioxide flowers (MnO₂ NFs) can oxidize TMB to etch gold nanorods (Au NRs), which can be inhibited by AA reduction to produce rich colors. Bacteria with varying ALP levels can be identified based on color changes and plasmon resonance wavelength signals produced from Au NRs. Furthermore, the conversion of RGB signals to digital signals and the use of linear discriminant analysis (LDA) allowed 99.57% accuracy in identifying multiple bacteria. It can simultaneously identify five foodborne pathogens across diverse environments (shrimp, meat, milk, etc.). This method may be useful for the rapid and simple identification of foodborne illnesses.

Colorimetric Sensing of Gram-Negative and Gram-Positive Bacteria Using 4-Mercaptophenylboronic Acid-Functionalized Gold Nanoparticles in the Presence of Polyethylene Glycol

Gold nanoparticles (GNPs) have been used as detection probes for rapid and sensitive detection of various analytes, including bacteria. Here, we demonstrate a simple strategy for bacterial detection using GNPs functionalized with 4-mercaptophenylboronic acid (4-MPBA). 4-MPBA can interact with peptidoglycan or lipopolysaccharides present in bacterial organelles. After the addition of a high concentration of sodium hydroxide (NaOH), the functionalization of the surface of 50 nm GNPs with 4-MPBA (4-MPBA@GNPs) in the presence of polyethylene glycol results in a color change because of the aggregation of 4-MPBA@GNPs. This color change is dependent on the amount of bacteria present in the tested samples. Escherichia coli (E. coli) K-12 and Staphylococcus aureus (S. aureus) are used as Gram-negative and Gram-positive bacterial models, respectively. The color change can be detected within an hour by the naked eye. A linear relationship is observed between bacterial concentrations and the absorbance intensity at 533 nm; R ² values of 0.9152 and 0.8185 are obtained for E. coli K-12 and S. aureus, respectively. The limit of detection of E. coli K-12 is ∼2.38 × 10² CFU mL^-1 and that of S. aureus is ∼4.77 × 10³ CFU mL^-1. This study provides a promising approach for the rapid detection of target Gram-negative and Gram-positive bacteria.

Recent Progress in Sensor Arrays: From Construction Principles of Sensing Elements to Applications

The traditional sensors are designed based on the "lock-and-key" strategy with high selectivity and specificity for detecting specific analytes, which however are not suitable for detecting multiple analytes simultaneously. With the help of pattern recognition technologies, the sensor arrays excel in distinguishing subtle changes caused by multitarget analytes with similar structures in a complex system. To construct a sensor array, the multiple sensing elements are undoubtedly indispensable units that will selectively interact with targets to generate the unique "fingerprints" based on the distinct responses, enabling the identification among various analytes through pattern recognition methods. This comprehensive review mainly focuses on the construction strategies and principles of sensing elements, as well as the applications of sensor array for identification and detection of target analytes in a wide range of fields. Furthermore, the present challenges and further perspectives of sensor arrays are discussed in detail.

Colorimetric Sensors for Chemical and Biological Sensing Applications

Colorimetric sensors have been widely used to detect numerous analytes due to their cost-effectiveness, high sensitivity and specificity, and clear visibility, even with the naked eye. In recent years, the emergence of advanced nanomaterials has greatly improved the development of colorimetric sensors. This review focuses on the recent (from the years 2015 to 2022) advances in the design, fabrication, and applications of colorimetric sensors. First, the classification and sensing mechanisms of colorimetric sensors are briefly described, and the design of colorimetric sensors based on several typical nanomaterials, including graphene and its derivatives, metal and metal oxide nanoparticles, DNA nanomaterials, quantum dots, and some other materials are discussed. Then the applications, especially for the detection of metallic and non-metallic ions, proteins, small molecules, gas, virus and bacteria, and DNA/RNA are summarized. Finally, the remaining challenges and future trends in the development of colorimetric sensors are also discussed.

Single-Probe-Based Colorimetric and Photothermal Dual-Mode Identification of Multiple Bacteria

Effective identification of multiple pathogenic bacteria in unknown samples is important for disease prevention and control but remains a challenge yet. A single-mode array-based sensing approach is simple and sensitive, but it usually relies on the use of multiple cross-reactive receptors to construct sensor arrays, which is cumbersome and insufficiently accurate. Here, we developed a sensor array with colorimetric and photothermal dual mode of differentiating multiple pathogenic bacteria. The sensor array was based on boronic acid-functionalized Au-Fe₃O₄ nanoparticles (BA-GMNPs), which not only possess localized surface plasmon resonance properties, showing a burgundy color similar to that of AuNPs, but also exhibit mild superparamagnetism, allowing for the differentiation of bacteria before and after binding to the nanoparticles. Immobilization of BA-GMNPs on the bacterial cell surface by covalent bonding would diminish NaCl-induced assembly of BA-GMNPs. Different BA-GMNPs@bacterial complexes differed in their ability to resist assembly and produced different colorimetric and photothermal response signals. A unique molecular fingerprint of each bacterium was obtained by linear discriminant analysis of the response patterns, demonstrating an effective differentiation among the six species studied. Compared with single-mode sensing arrays based on multiple receptors, this method only requires the preparation of a single nanomaterial, which produces two signal outputs for the identification of multiple bacteria with better differentiation. It can distinguish not only multiple pathogenic bacteria but also Gram-negative and Gram-positive bacteria, and, more importantly, it can perform preliminary discrimination of unknown samples.

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

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

Recent Advances in Colorimetric Sensors Based on Gold Nanoparticles for Pathogen Detection

Infectious pathogens cause severe threats to public health due to their frightening infectivity and lethal capacity. Rapid and accurate detection of pathogens is of great significance for preventing their infection. Gold nanoparticles have drawn considerable attention in colorimetric biosensing during the past decades due to their unique physicochemical properties. Colorimetric diagnosis platforms based on functionalized AuNPs are emerging as a promising pathogen-analysis technique with the merits of high sensitivity, low-cost, and easy operation. This review summarizes the recent development in this field. We first introduce the significance of detecting pathogens and the characteristics of gold nanoparticles. Four types of colorimetric strategies, including the application of indirect target-mediated aggregation, chromogenic substrate-mediated catalytic activity, point-of-care testing (POCT) devices, and machine learning-assisted colorimetric sensor arrays, are systematically introduced. In particular, three biomolecule-functionalized AuNP-based colorimetric sensors are described in detail. Finally, we conclude by presenting our subjective views on the present challenges and some appropriate suggestions for future research directions of colorimetric sensors.

Amine-Functionalized Silane-Assisted Preparation of AgNP-Deposited α-Ni(OH)2 Composite Materials and Their Application in Hg2+ Ion Sensing

A facile synthetic methodology for the deposition of different concentrations of Ag nanoparticles (AgNPs) on α-Ni(OH)₂ sheets (α-Ni₁(OH)₂-Ag_0.5, α-Ni₁(OH)₂-Ag₁, α-Ni₁(OH)₂-Ag₂, and α-Ni₁(OH)₂-Ag₃) is reported using N-[3-(trimethoxysilyl)propyl]diethylenetriamine (TPDT) silane. The TPDT aminosilane facilitates the formation of α-Ni(OH)₂ sheets and reduces the Ag⁺ precursor to AgNPs, leading to the deposition of AgNPs on α-Ni(OH)₂ sheets. UV-vis absorption spectroscopy, transmission microscopy analyses, X-ray photoelectron spectroscopy, X-ray diffraction, and attenuated total reflectance-Fourier transform infrared spectroscopy techniques were used to characterize the prepared α-Ni₁(OH)₂-Ag_0.5-3 composite materials. High-angle annular dark-field scanning transmission electron microscopy-energy-dispersive X-ray spectroscopy mapping images and scanning electron microscopy-energy-dispersive X-ray spectroscopy mapping images were recorded to understand the α-Ni₁(OH)₂-Ag composite sheet materials. The optical sensing property of α-Ni₁(OH)₂-Ag_0.5-3 composite materials toward toxic Hg²⁺ ions were investigated using a UV-vis absorption spectroscopy technique. The α-Ni₁(OH)₂-Ag₂ composite material showed selective sensing behavior.

Differential Sensing of Antibiotics Using Metal Ions and Gold Nanoclusters Based on TMB–H2O2 System

In the water system, antibiotic pollution significantly impacts the human body and the environment. Therefore, it is essential to quickly identify the types of antibiotics in the system and detect their concentration. It has been reported that many metal ions interact with antibiotics, and some of them can also change the enzyme-like catalytic properties of gold clusters (AuNCs). In the experiments, we found significant differences in the experimental results when different antibiotics and metal ions were placed in a TMB-H2O2 system with AuNCs as catalysts. Based on this result, we devised a simple and sensitive colorimetric method for the simultaneous detection of multiple antibiotics using AuNCs-metal ions as the sensor, a multifunctional microplate detector as the detection instrument, and LDA as the analytical method. This method was successfully applied for the identification of antibiotics and the detection of their concentrations in river water.

Metabolism-Triggered Colorimetric Sensor Array for Fingerprinting and Antibiotic Susceptibility Testing of Bacteria

The rapid identification and antibiotic susceptibility testing (AST) of bacteria would help us to accurately identify the infectious sources as well as guide the use of antibiotics, which are crucial for improving the survival rate and antimicrobial resistance. Herein, a colorimetric sensor array for bacteria fingerprinting was constructed with d-amino acid (d-AA)-modified gold nanoparticles (AuNPs) as probes (Au/d-AA). Bacteria can metabolize the d-AA, triggering the aggregation of AuNPs. Making use of different metabolic capabilities of bacteria toward different d-AA, eight kinds of bacteria including antibiotic-resistant bacteria and strains of the same bacterial species are successfully differentiated via learning the response patterns. Meanwhile, the sensor array also performs well in quantitative analysis of single bacterium and differentiation of bacteria mixtures. More interestingly, a rapid colorimetric AST approach has been developed based on the Au/d-AA nanoprobes by monitoring the d-AA metabolic activity of bacteria toward various antibiotic treatments. In this regard, the outlined work here would promote clinical practicability and facilitate antibiotic stewardship.

Rapid photothermal detection of foodborne pathogens based on the aggregation of MPBA-AuNPs induced by MPBA using a thermometer as a readout

Rapid and portable detection of foodborne pathogens is of great significance for food safety and public health. The colorimetric methods based on naked-eye have been demonstrated to be a suitable qualitative method for point-of-care testing (POCT). However, analytical instruments like a microplate reader must be needed for the quantitative assay. To overcome its limitation, we herein report a novel photothermal method for foodborne pathogens based on the photothermal effect of aggregated mercaptophenylboronic acid-functionalized AuNPs (MPBA-AuNPs) induced by MPBA to translate the colorimetric detection into a simple temperature measurement using thermometers as the readout. The aggregated AuNPs show higher photothermal conversion efficiency than well-separated AuNPs under 660 nm laser irradiation. In the presence of bacteria, MPBA-AuNPs will attach to the surface of bacteria and keep separated from aggregation induced by excess MPBA, resulting in a lower temperature increase under 660 nm laser irradiation. Using E. coli O157:H7 as a model target, a good linear relationship is observed between temperature increase and bacteria concentration from 1.00 × 10⁵-1.00 × 10⁹ cfu mL^-1 (R² = 0.9877) with a detection limit of 1.97 × 10⁴ cfu mL^-1, which is three orders of magnitude lower than of the MPBA-AuNPs-based colorimetric assays. The proposed photothermal method provided a universal platform for rapid and portable detection of broad-spectrum bacteria strains in real samples.

Triple-Function Au-Ag-Stuffed Nanopancakes for SERS Detection, Discrimination, and Inactivation of Multiple Bacteria

New strategies combining sensitive pathogenic bacterial detection and high antimicrobial efficacy are urgently desirable. Here, we report smart triple-functional Au-Ag-stuffed nanopancakes (AAS-NPs) exhibiting (1) controllably oxidative Ag-etching thickness for simultaneously obtaining the best surface-enhanced Raman scattering (SERS) enhancement and high Ag-loading antibacterial drug delivery, (2) expressive Ag⁺-accelerated releasing capability under neutral phosphate-buffered saline (PBS) (pH ∼ 7.4) stimulus and robust antibacterial effectiveness involving sustainable Ag⁺ release, and (3) three-in-one features combining specific discrimination, sensitive detection, and inactivation of different pathogenic bacteria. Originally, AAS-NPs were synthesized by particle growth of the selective Ag-etched Au@Ag nanoparticles with K₃[Fe(CN)₆], followed by the formation of an unstable Prussian blue analogue for specifically binding with bacteria through the cyano group. Using specific bacterial "fingerprints" resulting from the introduction of dual-function 4-mercaptophenylboronic acid (4-MPBA, serving as both the SERS tag and internal standard) and a SERS sandwich nanostructure that was made of bacteria/SERS tags/AAS-NPs, three bacteria (E. coli, S. aureus, and P. aeruginosa) were highly sensitively discriminated and detected, with a limit of detection of 7 CFU mL^-1. Meanwhile, AAS-NPs killed 99% of 1 × 10⁵ CFU mL^-1 bacteria within 60 min under PBS (pH ∼ 7.4) pretreatment. Antibacterial activities of PBS-stimulated AAS-NPs against S. aureus, E. coli, and P. aeruginosa were extraordinarily increased by 64-fold, 72-fold, and 72-fold versus PBS-untreated AAS-NPs, respectively. The multiple functions of PBS-stimulated AAS-NPs were validated by bacterial sensing, inactivation in human blood samples, and bacterial biofilm disruption. Our work exhibits an effective strategy for simultaneous bacterial sensing and inactivation.

Single Probe-Based Chemical-Tongue Sensor Array for Multiple Bacterial Identification and Photothermal Sterilization in Real Time

Simple and efficient identification of multiple bacteria and sterilization in real time is of considerable significance for clinical diagnostics and quality control in food. Herein, a novel chemical-tongue sensor array with 3,3',5,5'-tetramethylbenzidine (TMB) as a single probe was developed for bacterial identification and photothermal elimination. The synthesized bimetallic palladium/platinum nanoparticles (Pd/Pt_NPs) present excellent catalytic capability that can catalyze TMB into oxidized TMB (oxTMB) with four feature absorption peaks. Bacteria have different ability on inhibiting the reaction between TMB and Pd/Pt_NPs. With the absorbance intensity of oxTMB at the four feature peaks as readout, nine kinds of bacteria including two drug-resistant bacteria can be successfully distinguished via linear discriminant analysis. Remarkably, oxTMB exhibits excellent photothermal properties and can effectively kill bacteria in real time under near-infrared laser irradiation. The strategy of selecting TMB as a single probe simplifies the experimental operation and reduces the time cost. Furthermore, the developed sensing system was used to promote the wound healing process of MRSA-infected mice in vivo. The investigation provides a promising simple and efficient strategy for bacterial identification and sterilization with a universal platform, which has great potential application in clinical diagnosis and therapy.

Ultrasensitive dynamic light scattering immunosensing platform for NT-proBNP detection using boronate affinity amplification

Herein, we reported a new dynamic light scattering (DLS) immunosensing technology for the rapid and sensitive detection of glycoprotein N-terminal pro-brain natriuretic peptide (NT-proBNP). In this design, the boronate affinity recognition based on the interaction of boronic acid ligands and cis-diols was introduced to amplify the nanoparticle aggregation to enable highly sensitive DLS transduction, thereby lowering the limit of detection (LOD) of the methodology. After covalently coupling with antibodies, magnetic nanoparticles (MNPs) were employed as the nanoprobes to selectively capture trace amount of NT-proBNP from complex samples and facilitate DLS signal transduction. Meanwhile, silica nanoparticles modified with phenylboronic acid (SiO₂@PBA) were designed as the crosslinking agent to bridge the aggregation of MNPs in the presence of target NT-proBNP. Owing to the multivalent and fast affinity recognition between NT-proBNP containing cis-diols and SiO₂@PBA, the developed DLS immunosensor exhibited charming advantages over traditional immunoassays, including ultrahigh sensitivity with an LOD of 7.4 fg mL⁻¹, fast response time (< 20 min), and small sample consumption (1 μL). The DLS immunosensor was further characterized with good selectivity, accuracy, precision, reproducibility, and practicability. Collectively, this work demonstrated the promising application of the designed boronate affinity amplified-DLS immunosensor for field or point-of-care testing of cis-diol-containing molecules.

We developed a new DLS immunosensing technology for the rapid and sensitive detection of glycoprotein NT-proBNP.

The boronate affinity recognition amplified nanoparticle aggregation was designed to enable highly sensitive DLS transduction.

The fabricated DLS immunosensor exhibited ultrahigh sensitivity with an LOD of 7.4 fg mL⁻¹, fast response time (< 20 min), and small sample consumption (1 μL).

This boronate affinity amplified-DLS immunosensor has broad prospects for field or point-of-care testing of cis-diol-containing molecules.

Tug-of-War between Covalent Binding and Electrostatic Interaction Effectively Killing E. coli without Detectable Resistance

Antimicrobial resistance in Gram-negative bacteria has become one of the leading causes of morbidity and mortality and a serious worldwide public health concern due to the fact that Gram-negative bacteria have an additional outer membrane protecting them from an unwanted compound invading. It is still very difficult for antimicrobials to reach intracellular targets and very challenging to treat Gram-negative bacteria with the current strategies. Here, we found that (o-(bromomethyl)phenyl)boronic acid was incorporated into poly((2-N,N-diethyl)aminoethyl acrylate) (PDEA), forming a copolymer (poly(o-B_n-DEA)) having both phenylboronic acid (B) and ((2-N,N-diethyl)amino) (DEA) units. Poly(o-B_n-DEA) exhibits very strong intramolecular B-N coordination, which could highly promote the covalent binding of phenylboronic acid with lipopolysaccharide (LPS) on the outer membrane of E. coli and lodge poly(o-B_n-DEA) on the LPS layer on the surface of E. coli. Meanwhile, the strong electrostatic interaction between poly(o-B_n-DEA) and the negatively charged lipid preferred tugging the poly(o-B_n-DEA) into the lipid bilayer of E. coli. The combating interactions between covalent binding and electrostatic interaction form a tug-of-war action, which could trigger the lysis of the outer membrane, thereby killing Gram-negative E. coli effectively without detectable resistance.

Disposable Paper-Based Biosensors for the Point-of-Care Detection of Hazardous Contaminations-A Review

The fast detection of trace amounts of hazardous contaminations can prevent serious damage to the environment. Paper-based sensors offer a new perspective on the world of analytical methods, overcoming previous limitations by fabricating a simple device with valuable benefits such as flexibility, biocompatibility, disposability, biodegradability, easy operation, large surface-to-volume ratio, and cost-effectiveness. Depending on the performance type, the device can be used to analyze the analyte in the liquid or vapor phase. For liquid samples, various structures (including a dipstick, as well as microfluidic and lateral flow) have been constructed. Paper-based 3D sensors are prepared by gluing and folding different layers of a piece of paper, being more user-friendly, due to the combination of several preparation methods, the integration of different sensor elements, and the connection between two methods of detection in a small set. Paper sensors can be used in chromatographic, electrochemical, and colorimetric processes, depending on the type of transducer. Additionally, in recent years, the applicability of these sensors has been investigated in various applications, such as food and water quality, environmental monitoring, disease diagnosis, and medical sciences. Here, we review the development (from 2010 to 2021) of paper methods in the field of the detection and determination of toxic substances.

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

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

Recent progress in the optical detection of pathogenic bacteria based on noble metal nanoparticles

Pathogenic bacteria have become a huge threat to social health and economy for their frighteningly infectious and lethal capacity. It is quite important to make a diagnosis in advance to prevent infection or allow a rapid treatment after infection. Noble metal nanoparticles, due to their unique physicochemical properties, especially optical properties, have drawn a great attention during the past decades and have been widely applied into all kinds of fields related to human health. By utilizing these noble metal nanoparticles, optical diagnosis platforms towards pathogenic bacteria have emerged continually, providing highly sensitive, selective, and particularly facile detection tools for clinic or point-of-care diagnosis. This review summarizes the recent development in this field. It begins with a brief introduction of pathogenic bacteria and noble metal nanoparticles. And then, optical detection methods are systematically discussed in three distinct aspects. In addition to these proof-of-concept methods, corresponding algorithms and point-of-care detection devices are also described. Finally, the review ends up with subjective views on present limitations and some appropriate advice for future research directions.

Array-Based Biosensors for Bacteria Detection: From the Perspective of Recognition

Array-based biosensors have shown as effective and powerful tools to distinguish intricate mixtures with infinitesimal differences among analytes such as nucleic acids, proteins, microorganisms, and other biomolecules. In array-based bacterial sensing, the recognition of bacteria is the initial step that can crucially influence the analytical performance of a biosensor array. Bacteria recognition as well as the signal readout and mathematical analysis are indispensable to ensure the discrimination ability of array-based biosensors. Strategies for bacteria recognition mainly include the specific interaction between biomolecules and the corresponding receptors on bacteria, the noncovalent interaction between materials and bacteria, and the specific targeting of bacterial metabolites. In this review, recent advances in array-based bacteria sensors are discussed from the perspective of bacteria recognition relying on the characteristics of different bacteria. Principles of bacteria recognition and signal readout for bacteria detection are highlighted as well as the discussion on future trends in array-based biosensors.

Array-based microbial identification upon extracellular aminoglycoside residue sensing

Sensitive and rapid identification of pathogenic microorganisms is of great importance for clinical diagnosis and treatment. In this study, we developed an ultrasensitive colorimetric sensor array (CSA) based on the interactions between aminoglycoside antibiotics (AMGs) and Ag nanoparticles decorated with β-cyclodextrin (AgNPs@β-CD) to discriminate microorganisms quickly and accurately. Microorganisms can absorb different amounts of AMGs after incubation. Upon the addition of AgNPs@β-CD, the corresponding extracellular AMG residues will bind to AgNPs@β-CD, leading to color changes due to the modifications in localized surface plasmon resonance. The array was developed using 4 AMGs as sensing elements and AgNPs@β-CD as the colorimetric probe to generate a unique colorimetric response pattern for each microorganism. Standard chemometric methods indicated excellent discrimination among 20 microorganisms at low concentrations of 2 × 10⁶ CFU/mL. Therefore, this ultrasensitive CSA can be used for microbial discrimination portably and efficiently. Importantly, the concentration of microbial discrimination by our array is much lower than that of prior CSAs. This method of extracellular residue sensing also provided a new strategy to improve the sensitivity of conventional CSA in the discrimination of microorganisms, to measure the amount of intercellular uptake of AMGs by microorganisms, and to screen drugs that can easily be accumulated by the pathogenic microorganisms.

Lanthanide-functionalized metal-organic frameworks based ratiometric fluorescent sensor array for identification and determination of antibiotics

Antibiotics have made great contributions to the improvement of human health and life quality. However, the current abuse of antibiotics not only has a serious impact on the environment, but also endangers people's health. For this reason, the simultaneous identification and accurate determination of as many antibiotics in the environment, food and organisms as possible is critical. Herein, a ratiometric fluorescent sensor array based on Eu³⁺ and Tb³⁺ co-doped metal-organic frameworks (MOFs) was fabricated. Benefiting from the sensitization of the organic ligands to Eu³⁺ and Tb³⁺, the reaction of MOFs with various antibiotics resulted in different responses to the ratio of fluorescent intensity at 545 nm and 616 nm (F₅₄₅/F₆₁₆). After these responses were differentiated by principal component analysis (PCA), totally eight kinds of 25 antibiotics were well distinguished with the existence of interfering substances. The proposed sensor array exhibited high accuracy (98%) for the identification of 48 unknown samples in water and outstanding quantitative ability for the mixture of antibiotics. Finally, the practicability of the sensor array for the analysis of real samples was proved. In this strategy, we have not only provided an efficient way for the comprehensive identification and determination of antibiotics, but also promised new opportunities for the development of ratiometric signal based sensor array.

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

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

Label-free silver triangular nanoplates for spectrophotometric determination of catecholamines and their metabolites

A novel method towards spectrophotometric determination of catecholamines and their metabolites differing in their functional groups has been developed. This method is based on a change in morphology of silver triangular nanoplates upon the action of cateсholamines and their metabolites, which is manifested by the decrease of the nanoparticle local surface plasmon resonance (LSPR) band intensity or its shift to the short-wavelength region of the spectrum. The shift value of the LSPR band or the change of its intensity increases with increasing concentration of catecholamines or their metabolites, which is proposed for their spectrophotometric determination. The limits of detection of catecholamines and their metabolites under selected conditions increase in the series homovanillic acid < vanillylmandelic acid < L-epinephrine < L-norepinephrine < dopamine and are 0.25, 1.2, 3.0, 64, and 130 μmol L^-1, respectively. The selectivity of the proposed method was assessed using vanillylmandelic acid as example. It was found that the determination of vanillylmandelic acid does is not interfered in the presence of 4000-fold excess of Na⁺, K⁺, CH₃COO^-, and 1000-fold excess of Mg²⁺, Ca²⁺, Al³⁺, NO₃^-. The method also allows for the selective determination of vanillylmandelic acid in the presence of a 1000-fold excess of structurally related substances that do not contain either a catechol fragment or an electron donor substituent. The proposed approach was successfully applied to the determination of catecholamines in pharmaceuticals and artificial urine. Graphical abstract.

A Comparative Study on the Oxidation of Label-Free Silver Triangular Nanoplates by Peroxides: Main Effects and Sensing Applications

Nowadays, analytical systems based on silver triangular nanoplates (AgTNPs) have been shown as good prospects for chemical sensing. However, they still remain relatively poorly studied as colorimetric probes for sensing various classes of compounds. This study shows that these nanoparticles are capable of being oxidized by peroxides, including both hydrogen peroxide and its organic derivatives. The oxidation was found to result in a decrease in the AgTNPs' local surface plasmon resonance band intensity at 620 nm. This was proposed for peroxide-sensitive spectrophotometric determination. Five peroxides differing in their structure and number of functional groups were tested. Three of them easily oxidized AgTNPs. The effects of a structure of analytes and main exterior factors on the oxidation are discussed. The detection limits of peroxides in the selected conditions increased in the series peracetic acid < hydrogen peroxide < tert-butyl hydroperoxide, coming to 0.08, 1.6 and 24 μmol L^-1, respectively. tert-Butyl peroxybenzoate and di-tert-butyl peroxide were found to have no effect on the spectral characteristics of AgTNPs. By the example of hydrogen peroxide, it was found that the determination does not interfere with 100-4000-fold quantities of common inorganic ions. The proposed approach was successfully applied to the analysis of drugs, cosmetics and model mixtures.

Colorimetric identification of lanthanide ions based on two carboxylic acids as an artificial tongue

We report a colorimetric array, which consists of two carboxylic acids (quinolinic acid (QA), tannic acid (TCA)) as the sensor element and Eriochrome Black T (EBT) as the colorimetric signal readout. The assay is based on coordination binding between lanthanide ions and EBT, and between lanthanide ions and the carboxylic acids. The competitive binding of lanthanide ions with the carboxylic acids and EBT leads to the change in absorbance and color of the solutions. To test the efficacy of our sensor array, the sensor array was exposed to five target lanthanide ions (La³⁺, Sm³⁺, Eu³⁺, Gd³⁺ and Yb³⁺) with diverse concentrations (10, 50, 100, 200, 300, 400, and 500 nM). Linear discriminant analysis (LDA) results show that the sensor array can identify the five lanthanide ions, with a low discrimination limit of 10 nM. More importantly, the sensor array realizes fast discrimination of lanthanide ions in river samples, showing potential in environmental monitoring.