Fluorescent Sensor Array for Highly Efficient Microbial Lysate Identification through Competitive Interactions

Visual and real-time detection of the critical micelle concentration of nonionic surfactants using a supramolecular aggregate probe responsive to stable micelles

The critical micelle concentration (CMC) is considered one of the important parameters for evaluating and comparing surfactants. We have developed a novel method for detecting the CMC of nonionic surfactants, based on the environmentally responsive characteristics of cyanine dyes probes. Notably, this method exhibits high sensitivity, visual real-time monitoring capabilities, and robust anti-interference properties. The method remains effective even under alterations in pH (2-12), metal ion concentrations (0-150 mM of K+, Na+, Ca2+) and salinity levels (0-20 g/L). Furthermore, the method has been successfully applied to the analysis of real water such as lake water, water flooding, and oil-field sewage containing polymers, demonstrating its good applicability. This marks the first instance where we establish the application of detecting the CMC of nonionic surfactants using cyanine dye probes, offering a fresh perspective for developing highly sensitive, visual, real-time, and interference-resistant CMC detection methodologies.

Sensing Microorganisms Using Rapid Detection Methods: Supramolecular Approaches

Supramolecular chemistry relies on the dynamic association/dissociation of molecules through non-covalent interactions. These interactions of a self-assembled system can be strategically exploited for sensing several microorganisms. Moreover, supramolecular systems can also be combined with other functional components like nanoparticles, self-assembled monolayers, and microarray systems to produce multicomponent sensors with higher sensitivity and lower detection time. In this review, we will discuss how cutting-edge supramolecular chemistry has enabled scientists to develop microbial biosensors with high reliability and rapid detection time. Moreover, they produce high-throughput operations, real-time monitoring, extensive operation platforms, and cost-effective production. This review can serve as a conceptual background for understanding state-of-the-art rapid detection methods of microbial biosensing.

Fluorescence sensor array for highly sensitive pattern recognition of biothiols in food based on tricolor upconversion luminescence metal-organic frameworks

Fluorescence nanomaterial sensors have exhibited excellent application potential in biothiols analyses. The fluorescence sensor arrays constructed from upconversion luminescence metal-organic frameworks nanocomposites (LMOFs) can provide impressive discrimination and exquisite fingerprinting capabilities for extremely similar analytes. Herein, an upconversion fluorescence sensor array based on LMOFs featuring UiO-type metal-organic frameworks-functionalized lanthanide-doped upconversion nanoparticles was proposed, wherein Cu2+ can make the fluorescence quenching of LMOFs and preferentially bind biothiols to recover fluorescence in different degrees forming unique fingerprinting. The fluorescence sensor array displayed an excellent pattern recognition for five biothiols (glutathione, homocysteine, N-acetylcysteine, and L/D-cysteine) even at 50 µM by linear discriminant analysis, and the discernment for the enantiomers of L/D-cysteine, as well as the accurate identification (90.0% accuracy) of biothiols in food samples (tea beverage and white wine). Such fluorescence sensor array might provide a simple and efficient detection method for biothiols.

Tuning multispectral fluorescence quantum dot-based identification of short-length amyloid β peptides by applying Cu(II) ions

Currently available methods for detecting amyloid β (Aβ) derivatives are mainly dedicated to determining the long forms Aβ1-42 and Aβ1-40. At the same time, the number of physiologically occurring Aβ analogs is much higher, including those truncated at the N- and C-termini. Their identification using standard methods is challenging due to the structural similarity of various Aβ analogs, but could highly benefit from both biomarkers discovery and pathophysiological studies of Alzheimer's disease. Therefore a "chemical tongue" sensing strategy was employed for the detection of seven Aβ peptide derivatives: Aβ1-16, Aβ4-16, Aβ4-9, Aβ5-16, Aβ5-12, Aβ5-9, Aβ12-16. The proposed sensing system is based on competitive interactions between quantum dots, Cu(II) ions, and Aβ peptides, providing unique fluorescence fingerprints useful for the identification of analytes. After carefully evaluating the Aβ sample preparation protocol, perfect determination of all studied Aβ peptides was achieved using partial least square-discriminant analysis (PLS-DA). The developed PLS-DA models are characterized by excellent accuracy, sensitivity, precision, and specificity of analyte determination, emphasizing the potential of the proposed sensing strategy.

A Supramolecular Fluorescent Sensor Array Composed of Conjugated Fluorophores and Cucurbit[7]uril for Bacterial Recognition

Bacterial infections have emerged as a significant contributor to global mortality and morbidity rates. Herein, we introduce a dual fluorescence "turn-on" supramolecular sensor array composed of three assembled complexes (C1-C3), formed from three positively charged fluorophores (A1-A3) and one cucurbit[7]uril (CB[7]). The ability of this three-element array to simultaneously recognize 10 bacterial species within just 30 s was remarkable, boasting an impressive 100% accuracy. Additionally, the array excelled at distinguishing among various bacterial mixtures and enabled the quantitative detection of common bacterial strains. Notably, it has been skillfully applied to differentiate 10 bacterial samples in urine, achieving excellent differentiation and showcasing promising potential for medical diagnostic applications.

Expanding Our Horizons: AIE Materials in Bacterial Research

Bacteria share a longstanding and complex relationship with humans, playing a role in protecting gut health and sustaining the ecosystem to cause infectious diseases and antibiotic resistance. Luminogenic materials that share aggregation-induced emission (AIE) characteristics have emerged as a versatile toolbox for bacterial studies through fluorescence visualization. Numerous research efforts highlight the superiority of AIE materials in this field. Recent advances in AIE materials in bacterial studies are categorized into four areas: understanding bacterial interactions, antibacterial strategies, diverse applications, and synergistic applications with bacteria. Initial research focuses on visualizing the unseen bacteria and progresses into developing strategies involving electrostatic interactions, amphiphilic AIE luminogens (AIEgens), and various AIE materials to enhance bacterial affinity. Recent progress in antibacterial strategies includes using photodynamic and photothermal therapies, bacterial toxicity studies, and combined therapies. Diverse applications from environmental disinfection to disease treatment, utilizing AIE materials in antibacterial coatings, bacterial sensors, wound healing materials, etc., are also provided. Finally, synergistic applications combining AIE materials with bacteria to achieve enhanced outcomes are explored. This review summarizes the developmental trend of AIE materials in bacterial studies and is expected to provide future research directions in advancing bacterial methodologies.

Covalent Organic Frameworks-Based Fluorescence Sensor Array and QSAR Study for Identification of Energetic Heterocyclic Compounds

The accurate identification of energetic heterocyclic compounds (EHCs) is of great significance in munition assessment, environmental monitoring, and biosafety but remains largely underexplored. Herein, a covalent organic frameworks-based fluorescence sensor array (COFx sensor array) for efficient screening of EHCs is reported. The topologies of the COFs were rationally designed by modulating the pore sizes and linkage strategies to achieve the simplified sensor array. Eighteen EHC representatives, including single-, dual-, and three-ring EHCs with multivariate substructures, were successfully discriminated ranging from 10 μM to 1 mM. The sensor array showed robust selectivity against a wide range of interferences. The quantitative structure-activity relationship (QSAR) analysis has been conducted for the mechanistic study of the sensor array. Three multiple linear regression models have been established using molecular descriptors to evaluate and predict Stern-Volmer coefficient values, achieving explicit correlation between EHC structures and the signal outputs of the sensor array. Five molecular descriptors are retained to reveal the governing factors of the sensor array resolution. The QSAR analysis facilitates the design and development of the COFx sensor array, offering a new approach for customized multivariate analysis.

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.

A Dual Fluorescence Turn-On Sensor Array Formed by Poly(para-aryleneethynylene) and Aggregation-Induced Emission Fluorophores for Sensitive Multiplexed Bacterial Recognition

Bacterial infections have emerged as the leading causes of mortality and morbidity worldwide. Herein, we developed a dual-channel fluorescence "turn-on" sensor array, comprising six electrostatic complexes formed from one negatively charged poly(para-aryleneethynylene) (PPE) and six positively charged aggregation-induced emission (AIE) fluorophores. The 6-element array enabled the simultaneous identification of 20 bacteria (OD600=0.005) within 30s (99.0 % accuracy), demonstrating significant advantages over the array constituted by the 7 separate elements that constitute the complexes. Meanwhile, the array realized different mixing ratios and quantitative detection of prevalent bacteria associated with urinary tract infection (UTI). It also excelled in distinguishing six simulated bacteria samples in artificial urine. Remarkably, the limit of detection for E. coli and E. faecalis was notably low, at 0.000295 and 0.000329 (OD600), respectively. Finally, optimized by diverse machine learning algorithms, the designed array achieved 96.7 % accuracy in differentiating UTI clinical samples from healthy individuals using a random forest model, demonstrating the great potential for medical diagnostic applications.

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.

Boronic Acid-Decorated Carbon Dot-Based Semiselective Multichannel Sensor Array for Cytokine Discrimination and Oral Cancer Diagnosis

Cytokines are essential components of the immune system and are recognized as significant biomarkers. However, detection of a single cytokine is not precise and reliable enough to satisfy the requirements for diagnosis. Herein, we developed a pattern recognition-based method for the multiplexed sensing of cytokines, which involves three-color-emitting boronic acid-decorated carbon dots (BCDs) and arginine-modified titanium carbide (Ti3C2 MXenes) as the sensor array. Initially, the fluorescence signals of the three BCDs were quenched by Ti3C2 MXenes. In the presence of cytokines, the fluorescence intensity of the BCDs was restored or further quenched by different cytokines. The fluorescence response occurs in two steps: first, boronic acid interacts with cis-diol functional groups of cytokines, and second, arginine headgroup selectively interacts with glycans. By exploiting the different competing binding of the BCDs and the cytokines toward Ti3C2 MXenes, seven cytokines and their mixtures can be effectively discriminated at a concentration of 20 ng mL-1. Furthermore, our sensor array demonstrated an excellent performance in classifying human oral cancer saliva samples from healthy individuals with clinically relevant specificity. The noninvasive method offers a rapid approach to cytokine analysis, benefiting early and timely clinical diagnosis and treatment.

Nano-based theranostic approaches for infection control: current status and perspectives

Nano-based theranostic platforms constructed from various nanomaterials possess unique advantages in tackling bacterial and fungal infections while detecting pathogenic cells, making them a potential modality for addressing global healthcare burdens.

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.

Serum-Based Detection of Liver Pathology Using a Fluorogenic Alkaline Phosphatase Probe

Development of "ultrahigh contrast" fluorogenic probes for trapping alkaline phosphatase (ALP) activities in human serum is highly desirable for clinical auxiliary diagnosis for hepatobiliary diseases. However, the intrinsic dilemma of incomplete ionization of intramolecular charge transfer (ICT)-based ALP fluorophores and autofluorescence interference of serum result in low sensitivity and accuracy. Given that unique halogen effects could lead to a drastic decrease in the pKa value and a significant enhancement in the fluorescence quantum yield, herein we report an enzyme-activatable near-infrared probe based on a difluoro-substituted dicyanomethylene-4H-chromenep for achieving fluorescent quantification of human serum ALP. Rational design strategy is demonstrated by altering the substituted halogen groups to well regulate the pKa for meeting the physiological precondition. Owing to the complete ionization at pH 7.4 with tremendous fluorescence enhancement, the difluoro-substituted DCM-2F-HP manifests a linear relationship between the emission intensity and ALP concentration in both solution and serum samples. Along with measuring 77 human serum samples, the DCM-2F-HP based fluorescence method not only exhibits significant correlations with clinical colorimetry, but also distinguishes ALP patients from healthy volunteers, as well as assessing the progress of liver disease, thus providing a potential toolbox for quantitatively detecting ALP and warning the stage of hepatopathy.

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.

How Exactly Do AIEgens Target Bacteria? Leveraging the Targeting Mechanism to Design Sensitive Fluorescent Immunosensors

Aggregation-induced emission luminogens (AIEgens) are promising candidates for bacterial imaging and detection because they can "Light-Up" pathogenic bacteria without complicated labeling or washing steps. However, there have been few in-depth analyses of the intrinsic mechanism underlying their utility as fluorescence probes for targeting bacteria. Therefore, using large-scale molecular dynamics simulations, we investigated the mechanism of their bacterial "Light-Up" behavior with N,N-diphenyl-4-(7-(pyridin-4-yl)benzo[c][1,2,5]thiadiazol-4-yl) aniline functionalized with 1-bromoethane (TBP-1). We propose that the triphenylamine motif of TBP-1, rather than the positively charged pyridine group, first contacts the cell membrane. After TBP-1 completely inserts into the cell membrane, the hydrophobic triphenylamine motif localizes in the hydrophobic core of the cell membrane, restricting the molecular variation of TBP-1, which induces the fluorescent "turn-on" and bacterial "Light-Up." On this basis, we established a heterogeneous lateral flow immunoassay (LFIA) for the detection of foodborne pathogens. The LFIA system showed improved sensitivity with a limit of detection as low as 10³ CFU mL^-1 and strong specificity. Our protocol opened an effective shortcut to the design of more efficient AIEgens and novel AIEgens-based immunoassays.

A Polymer-Based Multichannel Sensor for Rapid Cell-Based Screening of Antibiotic Mechanisms and Resistance Development

Antibiotic resistance presents a critical threat to public health, necessitating the rapid development of novel antibiotics and an appropriate choice of therapeutics to combat refractory bacterial infections. Here, we report a high-throughput polymer-based sensor platform that rapidly (30 min) profiles mechanisms of antibiotic activity. The sensor array features three fluorophore-conjugated polymers that can detect subtle antibiotic-induced phenotypic changes on bacterial surfaces, generating distinct mechanism-based fluorescence patterns. Notably, discrimination of different generations of antibiotic resistance was achieved with high efficiency. This sensor platform combines trainability, simplicity, and rapid screening into a readily translatable platform.

Fluorescence Analysis of Circulating Exosomes for Breast Cancer Diagnosis Using a Sensor Array and Deep Learning

Emerging liquid biopsy methods for investigating biomarkers in bodily fluids such as blood, saliva, or urine can be used to perform noninvasive cancer detection. However, the complexity and heterogeneity of exosomes require improved methods to achieve the desired sensitivity and accuracy. Herein, we report our study on developing a breast cancer liquid biopsy system, including a fluorescence sensor array and deep learning (DL) tool AggMapNet. In particular, we used a 12-unit sensor array composed of conjugated polyelectrolytes, fluorophore-labeled peptides, and monosaccharides or glycans to collect fluorescence signals from cells and exosomes. Linear discriminant analysis (LDA) processed the fluorescence spectral data of cells and cell-derived exosomes, demonstrating successful discrimination between normal and different cancerous cells and 100% accurate classification of different BC cells. For heterogeneous plasma-derived exosome analysis, CNN-based DL tool AggMapNet was applied to transform the unordered fluorescence spectra into feature maps (Fmaps), which gave a straightforward visual demonstration of the difference between healthy donors and BC patients with 100% prediction accuracy. Our work indicates that our fluorescent sensor array and DL model can be used as a promising noninvasive method for BC diagnosis.

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

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

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.

Simpler Procedure and Improved Performance for Pathogenic Bacteria Analysis with a Paper-Based Ratiometric Fluorescent Sensor Array

Bacterial infections are the leading cause of morbidity and mortality in the world, particularly due to a delay in treatment and misidentification of the bacterial species causing the infection. Therefore, rapid and accurate identification of these pathogens has been of prime importance. The conventional diagnostic techniques include microbiological, biochemical, and genetic analyses, which are time-consuming, require large sample volumes, expensive equipment, reagents, and trained personnel. In response, we have now developed a paper-based ratiometric fluorescent sensor array. Environment-sensitive fluorescent dyes (3-hydroxyflavone derivatives) pre-adsorbed on paper microzone plates fabricated using photolithography, upon interaction with bacterial cell envelopes, generate unique fluorescence response patterns. The stability and reproducibility of the sensor array response were thoroughly investigated, and the analysis procedure was refined for optimal performance. Using neural networks for response pattern analysis, the sensor was able to identify 16 bacterial species and recognize their Gram status with an accuracy rate greater than 90%. The paper-based sensor was stable for up to 6 months after fabrication and required 30 times lower dye and sample volumes as compared to the analogous solution-based sensor. Therefore, this approach opens avenues to a state-of-the-art diagnostic tool that can be potentially translated into clinical applications in low-resource environments.

A multifunctional colorimetric sensor array for bacterial identification and real-time bacterial elimination to prevent bacterial contamination

The constructed sensor array has simple operation and successfully integrates bacterial identification and inactivation.

AIEgens for Bacterial Imaging and Ablation

Accurate and sensitive diagnosis of pathogenic bacterial infection is a fundamental first step for correct bacteria management, helping to avoid the development of drug-resistant bacteria caused by the inappropriate use and overuse of antibiotics. Fluorescence probes as a promising visual tool can help identify pathogens rapidly and reliably. However, rigidly structured traditional fluorescence probes generally suffer from the drawback of aggregation-caused quenching (ACQ) effect, which greatly undermines their advantages with respect to sensitivity. Luminogens with aggregation-induced emission properties, namely AIEgens, can overcome the ACQ effect and certain AIEgen-based materials are capable of generating reactive oxygen species (ROS) in the aggregate states. Hence, they have become powerful tools for imaging and killing bacteria. This review summarizes the recent advances in AIEgens for the diagnosis and treatment of pathogen infections. Special attention has been paid to the molecular design, the application in bacterial imaging and ablation in vitro and in vivo, and the biocompatibility of AIEgens. Finally, the challenges and prospects are discussed in terms of using AIEgens to advance precision therapies for pathogen infections.

Fluorescent Ensemble Sensors and Arrays Based on Surfactant Aggregates Encapsulating Pyrene-Derived Fluorophores for Differentiation Applications

Surfactant assemblies have drawn great attention in fabricating fluorescent sensors as they can provide advantages such as easy preparation, low cost, aqueous detection, high fluorescence stability, high sensitivity to external stimuli, etc. We have devoted the past few years to fluorescent cross-reactive sensors and arrays that are advantageous in differentiating similar analytes and analyzing mixed samples. In this Spotlight on Applications, we introduce our recent advances in developing surfactant assembly-based fluorescent sensors and arrays for discrimination applications. Besides using surfactant assemblies encapsulating fluorophores to fabricate multiple-element-based sensor arrays, we particularly proposed to take advantage of modulation effect of dynamic surfactant assemblies on the photophysical properties of encapsulated fluorophores to construct single-system-based discriminative sensors, which have been successfully applied in differentiation of multiple metal ions and various proteins. The applications of surfactant assembly-based sensors for the detection and discrimination of thiols, amino acids, and explosives are also introduced. Finally, the prospects of further efforts for improving surfactant ensemble sensors and their challenges are discussed.

Imaging, Identification and Inhibition of Microorganisms Using AIEgens

Microorganisms, including bacteria, viruses and fungi, are ubiquitous in nature. Some are extremely beneficial to life on Earth, whereas some cause diseases and disrupt normal human physiology. Pathogenic microorganisms can also undergo mutations and develop resistance to antimicrobial agents, which complicates diagnostic and therapeutic regimens. This calls for continuing efforts to develop new strategies and tools that can provide fast, sensitive and accurate diagnosis, as well as effective treatment of ever-evolving infectious diseases. Aggregation-induced emission luminogens (AIEgens) have shown promise in imaging, identification and inhibition of various microbial species. Compared to conventional organic fluorophores, AIEgens can offer improved photostability, and have found utilities in imaging microorganisms. AIEgens have been shown to detect microbial viability and differentiate among different microbial strains. Theranostic AIEgens that integrate imaging and killing of microbes have also been developed. This review highlights examples in the literature where AIEgens have been employed as molecular probes in the imaging, discrimination and killing of bacteria, viruses and fungi.

Single gold nanocluster probe-based fluorescent sensor array for heavy metal ion discrimination

There is a continuing high demand to design effective sensors for the determination of heavy metal ions (HMIs) since they are hazardous to both human health and the environment. In this study, we reported a facile fluorescent sensor array for rapid discrimination of HMIs based on a single gold nanocluster (AuNC) probe. This AuNC probe was prepared by using 2-mercapto-1-methylimidazole (MMI) as a ligand and polyvinypyrrolidone (PVP) as a dispersing agent. The fluorescence emission of PVP/MMI-AuNC was observed to be closely related to the pH value of the aqueous solution, which displays yellow (λ_max = 512 nm) and red (λ_max = 700 nm) fluorescence at pH 12.0 and 6.0, respectively. Further experiments indicated that different HMIs can produce differential effects on the photoluminescence of PVP/MMI-AuNC and thus generate distinct fluorescent responses at 512 and 700 nm. On the basis of this phenomenon, a fluorescent sensor array based on the PVP/MMI-AuNC was then built by simply changing pH value in the sensor element. A total of seven HMIs had their unique response patterns and were successfully distinguished by hierarchical cluster analysis and linear discriminant analysis both in buffer solution and spiked water samples, achieving 100% identification accuracy. This study provides a simple and powerful fingerprinting sensing platform for multiple HMIs, showing broad application prospects in the field of environmental monitoring.

AIEgens for microbial detection and antimicrobial therapy

Pathogenic microbes can cause infections or diseases in hosts and they pose ongoing threats to human health. Antibiotics have been taken an active role in treating a wide variety of infections or diseases since they were first introduced in the 1940s. However, the emergence of antibiotic-resistant microbes makes these previously effective drugs invalid regrettably. So it is urgently needed to accelerate research and development for new antimicrobial systems and strategies. Recently, luminogens with aggregation-induced emission characteristics (AIEgens) have emerged as powerful fluorescent tools for microbial detection and antimicrobial therapy. In this review, we highlighted the latest advancements of AIEgen-based biofunctional materials and systems in this research field. AIE fluorescent probes have the advantages of excellent sensitivity and rapid response, which make them useful for ultrafast bacterial imaging, bacteria classification, and pathogen discrimination. Early microbial detection and identification could help us study the mechanism of antibiotic resistance more scientifically. Moreover, the AIEgens-based photosensitizers (AIE-PSs) with strong photosensitization show good performance on the efficient elimination of multidrug-resistant bacteria and intracellular bacteria. At the end of the review, a short perspective on aggregate science is concluded.

Polymer Electrochromism Driven by Metabolic Activity Facilitates Rapid and Facile Bacterial Detection and Susceptibility Evaluation

The electrochromism of a water-soluble naturally oxidized electrochromic polymer, ox-PPE, is harnessed for rapid and facile bacterial detection, discrimination, and susceptibility testing. The ox-PPE solution shows distinct colorimetric and spectroscopic changes within 30 min when mixed with live bacteria. For the underlying mechanism, it is found that ox-PPE responds to the reducing species (e.g. cysteine and glutathione) released by metabolically active bacteria. This reduction reaction is ubiquitous among various bacterial strains, with a noticeable difference that enables discrimination of Gram-negative and Gram-positive bacterial strains. Combining ox-PPE with antibiotics, methicillin-susceptible and -resistant S. aureus can be differentiated within 2.5 h. Proof-of-concept demonstration of ox-PPE for antimicrobial susceptibility testing is carried out by incubating E. coli with various antibiotics. The obtained minimum inhibition concentrations are consistent with the conventional culture-based methods, but with the procedure time significantly shortened to 3 h.

Direct Femtosecond Laser Printing of Silk Fibroin Microstructures

Fabrication of functional silk fibroin microstructures has extensive applications in biotechnology and photonics. Considerable progress has been made based on lithographic methods and self-assembly approaches. However, most methods require chemical modification of silk fibroin, which restricts the functionalities of the designed materials. At the same time, femtosecond laser-induced forward transfer (fs-LIFT) has been explored as a simple and attractive processing tool for microprinting of high-resolution structures. In this paper, we propose the use of LIFT with fs-pulses for creating high-resolution structures of regenerated silk fibroin (SF). Furthermore, upon adding Eu³⁺/Tb³⁺ complexes to SF, we have been able to demonstrate the printing by LIFT of luminescent SF structures with a resolution on the order of 2 μm and without material degradation. This approach provides a facile method for printing well-defined two-dimensional (2D) micropatterns of pure and functionalized SF, which can be used in a wide range of optical and biomedical applications.

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.

Functional Polymers and Polymer-Dye Composites for Food Sensing

The sensitive, safe, and portable detection of food spoilage is becoming unprecedentedly important because it is closely related to the public health and economic development, particularly given the globalization of food supply chain. However, the existing approaches for food monitoring are still limited to meet these requirements. To address this challenge, much research has been done to develop an ideal food sensor that can indicate food quality in real-time in a sensitive and reliable way. So far, many sensors such as time-temperature indicators, smart trademarks, colorimetric tags, electronic noses, and electronic tongues, have been developed and even commercialized. In this feature article, the recent progress of food sensors based on functional polymers, including the molecular design of polymer structures, sensing mechanisms, and relevant processing techniques to fabricate a variety of food sensor devices is reviewed.

AIEgens: An emerging fluorescent sensing tool to aid food safety and quality control

As a global public health problem, food safety has attracted increasing concern. To minimize the risk exposure of food to harmful ingredients, food quality and safety inspection that covers the whole process of "from farm to fork" is much desired. Fluorescent sensing is a promising and powerful screening tool for sensing hazardous substances in food and thus plays a crucial role in promoting food safety assurance. However, traditional fluorphores generally suffer the problem of aggregation-caused quenching (ACQ) effect, which limit their application in food quality and safety inspection. In this regard, luminogens with aggregation-induced emission property (AIEgens) showed large potential in food analysis since AIEgens effectively surmount the ACQ effect with much better detection sensitivity, accuracy, and robustness. In this contribution, we review the latest developments of food safety monitoring by AIEgens, which will focus on the molecular design of AIEgens and their sensing principles. Several examples of AIE-based sensing applications for screening food contaminations are highlighted, and future perspectives and challenges in this emerging field are tentatively elaborated. We hope this review can motivate new research ideas and interest to aid food safety and quality control, and facilitate more collaborative endeavors to advance the state-of-the-art sensing developments and reduce actual translational gap between laboratory research and industrial production.

Fluorescent Materials With Aggregation-Induced Emission Characteristics for Array-Based Sensing Assay

Array-based sensing is a powerful tool for identifying analytes in complex environments with unknown interferences. In array-based sensing, the sensors, which transduce binding details to signal outputs, are of crucial importance for identifying analytes. Aggregation-induced emission luminogens (AIEgens) enjoy the advantages of easy synthesis and high sensitivity, which enable them to facilely form a sensor pool through structural modifications and sensitively reflect the subtle changes associated with binding events. All these features make AIEgens excellent candidates for array-based sensing, and attempts have been made by several research groups to explore their potentials in array-based sensing. In this review, we introduce the recent progresses of employing AIEgens as sensors in sensing assays and in building up sensor arrays for identification of varied biological analytes, including biomolecules and bacteria. Examples are selected to illustrate the working mechanism, probe design and selection, capability of the sensor array, and implications of these sensing methods.

Surface chemistry modified upconversion nanoparticles as fluorescent sensor array for discrimination of foodborne pathogenic bacteria

BACKGROUND

The identification of foodborne pathogenic bacteria types plays a crucial role in food safety and public health. In consideration of long culturing times, tedious operations and the desired specific recognition elements in conventional methods, the alternative fluorescent sensor arrays can offer a high-effective approach in bacterial identification by using multiple cross-reactive receptors. Herein, we achieve this goal by constructing an upconversion fluorescent sensor array based on anti-stokes luminogens featuring a series of functional lanthanide-doped upconversion nanoparticles (UCNPs) with phenylboronic acid, phosphate groups, or imidazole ionic liquid. The prevalent spotlight effect of microorganism and the electrostatic interaction between UCNPs and bacteria endow such sensor array an excellent discrimination property.

RESULTS

Seven common foodborne pathogenic bacteria including two Gram-positive bacteria (Staphylococcus aureus and Listeria monocytogenes) and five Gram-negative bacteria (Escherichia coli, Salmonella, Cronobacter sakazakii, Shigella flexneri and Vibrio parahaemolyticus) are precisely identified with 100% accuracy via linear discriminant analysis (LDA). Furthermore, blends of bacteria have been identified accurately. Bacteria in real samples (tap water, milk and beef) have been effectively discriminated with 92.1% accuracy.

CONCLUSIONS

Current fluorescence sensor array is a powerful tool for high-throughput bacteria identification, which overcomes the time-consuming bacteria culture and heavy dependence of specific recognition elements. The high efficiency of whole bacterial cell detection and the discrimination capability of life and death bacteria can brighten the application of fluorescence sensor array.

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.

AIE-based theranostic systems for detection and killing of pathogens

Pathogenic bacteria, fungi and viruses pose serious threats to the human health under appropriate conditions. There are many rapid and sensitive approaches have been developed for identification and quantification of specific pathogens, but many challenges still exist. Culture/colony counting and polymerase chain reaction are the classical methods used for pathogen detection, but their operations are time-consuming and laborious. On the other hand, the emergence and rapid spread of multidrug-resistant pathogens is another global threat. It is thus of utmost urgency to develop new therapeutic agents or strategies. Luminogens with aggregation-induced emission (AIEgens) and their derived supramolecular systems with unique optical properties have been developed as fluorescent probes for turn-on sensing of pathogens with high sensitivity and specificity. In addition, AIE-based supramolecular nanostructures exhibit excellent photodynamic inactivation (PDI) activity in aggregate, offering great potential for not only light-up diagnosis of pathogen, but also image-guided PDI therapy for pathogenic infection.

A review on graphene-based nanocomposites for electrochemical and fluorescent biosensors

Biosensors with high sensitivity, selectivity and a low limit of detection, reaching nano/picomolar concentrations of biomolecules, are important to the medical sciences and healthcare industry for evaluating physiological and metabolic parameters.