Ratiometric Fluorescent Sensor Array as a Versatile Tool for Bacterial Pathogen Identification and Analysis

Machine Learning-Assisted Liquid Crystal Optical Sensor Array Using Cysteine-Functionalized Silver Nanotriangles for Pathogen Detection in Food and Water

The challenge of rapid identification of bacteria in food and water still persists as a major health problem. To tackle this matter, we have developed a single-probe liquid crystal (LC)-based optical sensing platform for the differentiation of five common bacterial strains, including Bacillus cereus, Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, and S. typhimurium, using cysteine-functionalized silver nanotriangles as signal enhancers. Unique optical patterns were generated from the interaction of the samples with the LC interface and captured by using a camera under polarized light. Pattern recognition was carried out based on image analysis and machine learning (ML) calculations. Among the various ML algorithms trained, Support Vector Machines had the best performance and were able to successfully discern the bacteria with 98.89% accuracy. A linear range of 10-106 CFU mL-1 and detection limits of under 10 CFU mL-1 were attained for all of the strains. The proposed method was tested with water, juice, and milk samples, and prediction accuracies of 95.83, 97.92, and 89.58%, respectively, were obtained. The proposed method offers a simple, cost-efficient solution for bacteria recognition.

Advances in Vibrio-related infection management: an integrated technology approach for aquaculture and human health

Vibrio species pose significant threats worldwide, causing mortalities in aquaculture and infections in humans. Global warming and the emergence of worldwide strains of Vibrio diseases are increasing day by day. Control of Vibrio species requires effective monitoring, diagnosis, and treatment strategies at the global scale. Despite current efforts based on chemical, biological, and mechanical means, Vibrio control management faces limitations due to complicated implementation processes. This review explores the intricacies and challenges of Vibrio-related diseases, including accurate and cost-effective diagnosis and effective control. The global burden due to emerging Vibrio species further complicates management strategies. We propose an innovative integrated technology model that harnesses cutting-edge technologies to address these obstacles. The proposed model incorporates advanced tools, such as biosensing technologies, the Internet of Things (IoT), remote sensing devices, cloud computing, and machine learning. This model offers invaluable insights and supports better decision-making by integrating real-time ecological data and biological phenotype signatures. A major advantage of our approach lies in leveraging cloud-based analytics programs, efficiently extracting meaningful information from vast and complex datasets. Collaborating with data and clinical professionals ensures logical and customized solutions tailored to each unique situation. Aquaculture biotechnology that prioritizes sustainability may have a large impact on human health and the seafood industry. Our review underscores the importance of adopting this model, revolutionizing the prognosis and management of Vibrio-related infections, even under complex circumstances. Furthermore, this model has promising implications for aquaculture and public health, addressing the United Nations Sustainable Development Goals and their development agenda.

Fast and accurate identification of pathogenic bacteria using excitation-emission spectroscopy and machine learning

Fast and reliable identification of pathogenic bacteria is of upmost importance to human health and safety. Methods that are currently used in clinical practice are often time consuming, require expensive equipment, trained personnel, and therefore have limited applications in low resource environments. Molecular identification methods address some of these shortcomings. At the same time, they often use antibodies, their fragments, or other biomolecules as recognition units, which makes such tests specific to a particular target. In contrast, array-based methods use a combination of reporters that are not specific to a single pathogen. These methods provide a more data-rich and universal response that can be used for identification of a variety of bacteria of interest. In this report, we demonstrate the application of the excitation-emission spectroscopy of an environmentally sensitive fluorescent dye for identification of pathogenic bacterial species. 2-(4'-Dimethylamino)-3-hydroxyflavone (DMAF) interacts with the bacterial cell envelope resulting in a distinct spectral response that is unique to each bacterial species. The dynamics of dye-bacteria interaction were thoroughly investigated, and the limits of detection and identification were determined. Neural network classification algorithm was used for pattern recognition analysis and classification of spectral data. The sensor successfully discriminated between eight representative pathogenic bacteria, achieving a classification accuracy of 85.8% at the species level and 98.3% at the Gram status level. The proposed method based on excitation-emission spectroscopy of an environmentally sensitive fluorescent dye is a powerful and versatile diagnostic tool with high accuracy in identification of bacterial pathogens.

Glucose-metabolism-triggered colorimetric sensor array for point-of-care differentiation and antibiotic susceptibility testing of bacteria

Simple and sensitive discrimination of multiple bacteria and antimicrobial susceptibility test (AST) are significant for food safety, clinical diagnosis and treatment. Herein, based on different metabolic ability of bacteria on glucose, we presented a colorimetric sensor array for point-of-care testing (POCT) of multiple bacteria with methyl red (MER), bromothymol blue (BTB) and bromocresol green (BCG) as probes. Different bacteria resulted in different color changes of three probes, which was converted to RGB (Red (R)/Green (G)/Blue (B)) signals by the color recognizer APP loaded on smartphone. The sensor array performed differentiation of eleven species of bacteria, achieving the quantitative analysis of individual bacteria in tap water and differentiation of bacterial mixtures. Interestingly, the sensor array can be used for AST and evaluating minimal inhibitory concentration (MIC) of antibiotics to bacteria. The research provided meaningful guidance for distinguishing multiple bacteria and evaluating MIC, presenting great potential in practical application.

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.

Triple-Emission Single Sensing Element-Enabled Ratiometric Fluorescent Array Identification of Multiple Antibiotics

Given that intricate toxicological profiles exist among different antibiotics and pose serious threats to the environment and human health, synchronous analysis of multiple residues becomes crucial. Sensor arrays show potential to achieve the above purpose, but it is challenging to develop easy-to-use and high-sensitivity tools because the state-of-the-art arrays often require more than one recognition unit and are monosignal dependent. Here we exquisitely designed a fluorescent nanoprobe (2-aminoterephthalic acid-anchored CdTe quantum dots with Eu3+ coordination, CdTe-ATPA-Eu3+) featuring triple emissions at the same excitation as the only element to fabricate a luminescent sensor array with ratiometric calculations for identifying multiple antibiotics. By taking tetracycline, chlortetracycline, doxycycline, oxytetracycline, penicillin G, and sulfamethoxazole as models, the six species exhibited distinguishable motivation or/and quenching impacts on the three emissions of CdTe-ATPA-Eu3+, which were employed as indicators to perform the ratiometric logical operation and further combined with pattern recognition analysis for multitarget determination. Evidently, such a design exhibits two advances: (1) with the triple-emission probe as the sole receptor requiring neither internal nor external adjustments, the fabricated array acts as an extremely facile tool for multianalyte detection; (2) the ratiometric calculations offer excellent sensitivity and reliability for high-performance determination. Consequently, accurate identification and quantification of individual antibiotics and their combinations at various levels were verified in both laboratory and practical matrices. Our work provides a new tool for simultaneously detecting multiple antibiotics, and it will inspire the development of advanced sensor arrays for multitarget analysis.

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.

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.

Rapid Fluorescence Sensor Guided Detection of Urinary Tract Bacterial Infections

Introduction

Urinary tract infections (UTI) are one of the most serious human bacterial infections affecting millions of people every year. Therefore, simple and reliable identification of the urinary tract pathogenic bacteria within a few minutes would be of great significance for diagnosis and treatment of clinical patients with UTIs. In this study, the fluorescence sensor was reported to guide the detection of urinary tract bacterial infections rapidly.

Methods

The Ami-AuNPs-DNAs sensor was fabricated by the amino-modified Au nanoparticles (Ami-AuNPs) and six DNAs signal molecules, which bound to the urinary tract pathogenic bacteria and generated corresponding response signals. Further, based on the collected response signals, identification was performed by principal component analysis (PCA) and linear discriminant analysis (LDA). The Ami-AuNPs and Ami-AuNPs-DNAs were characterized by transmission electron microscopy, UV−vis absorption spectrum, Fourier transform infrared spectrum, dynamic light scattering and zeta potentials. Thereafter, the Ami-AuNPs-DNAs sensor was used to discriminate and identify five kinds of urinary tract pathogenic bacteria. Moreover, the quantitative analysis performance towards individual bacteria at different concentrations were also evaluated.

Results

The Ami-AuNPs-DNAs sensor were synthesized successfully in terms of spherical, well-dispersed and uniform in size, which could well discriminate five main urinary tract pathogenic bacteria with unique fingerprint-like patterns and was sufficiently sensitive to determine individual bacteria with a detection limit to 1×10⁷ cfu/mL. Furthermore, the sensor had also been successfully applied to identify bacteria in urine samples collected from clinical UTIs.

Conclusion

The developed fluorescence sensor could be applied to rapid and accurate discrimination of urinary tract pathogenic bacteria and holds great promise for the diagnosis of the disease caused by bacterial infection.

One-Component Multichannel Sensor Array for Rapid Identification of Bacteria

Bacterial infections routinely cause serious problems to public health. To mitigate the impact of bacterial infections, sensing systems are urgently required for the detection and subsequent epidemiological control of pathogenic organisms. Most conventional approaches are time-consuming and highly instrument- and professional operator-dependent. Here, we developed a novel one-component multichannel array constructed with complex systems made from three modified polyethyleneimine as well as negatively charged graphene oxide, which provided an information-rich multimode response to successfully identify 10 bacteria within minutes via electrostatic interactions and hydrophobic interactions. Furthermore, the concentration of bacteria (from OD₆₀₀ = 0.025 to 1) and the ratio of mixed bacteria were successfully achieved with our smart sensing system. Our designed sensor array also exhibited huge potential in biological samples, such as in urine (OD₆₀₀ = 0.125, 94% accuracy). The way to construct a sensor array with minimal sensor element with abundant signal outputs tremendously saves cost and time, providing a powerful tool for the diagnosis and assessment of bacterial infections in the clinic.

Polymer-based chemical-nose systems for optical-pattern recognition of gut microbiota

Gut-microbiota analysis has been recognized as crucial in health management and disease treatment. Metagenomics, a current standard examination method for the gut microbiome, is effective but requires both expertise and significant amounts of general resources. Here, we show highly accessible sensing systems based on the so-called chemical-nose strategy to transduce the characteristics of microbiota into fluorescence patterns. The fluorescence patterns, generated by twelve block copolymers with aggregation-induced emission (AIE) units, were analyzed using pattern-recognition algorithms, which identified 16 intestinal bacterial strains in a way that correlates with their genome-based taxonomic classification. Importantly, the chemical noses classified artificial models of obesity-associated gut microbiota, and further succeeded in detecting sleep disorder in mice through comparative analysis of normal and abnormal mouse gut microbiota. Our techniques thus allow analyzing complex bacterial samples far more quickly, simply, and inexpensively than common metagenome-based methods, which offers a powerful and complementary tool for the practical analysis of the gut microbiome.

Cell-Based Chemical Safety Assessment and Therapeutic Discovery Using Array-Based Sensors

Synthetic chemicals are widely used in food, agriculture, and medicine, making chemical safety assessments necessary for environmental exposure. In addition, the rapid determination of chemical drug efficacy and safety is a key step in therapeutic discoveries. Cell-based screening methods are non-invasive as compared with animal studies. Cellular phenotypic changes can also provide more sensitive indicators of chemical effects than conventional cell viability. Array-based cell sensors can be engineered to maximize sensitivity to changes in cell phenotypes, lowering the threshold for detecting cellular responses under external stimuli. Overall, array-based sensing can provide a robust strategy for both cell-based chemical risk assessments and therapeutics discovery.

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.

Monitoring the Viral Transmission of SARS-CoV-2 in Still Waterbodies Using a Lanthanide-Doped Carbon Nanoparticle-Based Sensor Array

The latest epidemic of extremely infectious coronavirus disease 2019 (COVID-19) has created a significant public health concern. Despite substantial efforts to contain severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) within a specific location, shortcomings in the surveillance of predominantly asymptomatic infections constrain attempts to identify the epidemiological spread of the virus. Continuous surveillance of wastewater streams, including sewage, offers opportunities to track the spread of SARS-CoV-2, which is believed to be found in fecal waste. To demonstrate the feasibility of SARS-CoV-2 detection in wastewater systems, we herein present a novel facilely constructed fluorescence sensing array based on a panel of three different lanthanide-doped carbon nanoparticles (LnCNPs). The differential fluorescence response pattern due to the counterion-ligand interactions allowed us to employ powerful pattern recognition to effectively detect SARS-CoV-2 and differentiate it from other viruses or bacteria. The sensor results were benchmarked to the gold standard RT-qPCR, and the sensor showed excellent sensitivity (1.5 copies/μL) and a short sample-to-results time of 15 min. This differential response of the sensor array was also explained from the differential mode of binding of the LnCNPs with the surface proteins of the studied bacteria and viruses. Therefore, the developed sensor array provides a cost-effective, community diagnostic tool that could be potentially used as a novel epidemiologic surveillance approach to mitigate the spread of COVID-19.

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.

Carbon dots and gold nanoclusters assisted construction of a ratiometric fluorescent biosensor for detection of Gram-negative bacteria

A core-satellite nanocomposite was prepared by encapsulating the photostable blue carbon dots (BCDs) in the core of silica as the reference signal readout, and the target-sensitive gold nanoclusters (AuNCs) covalently linked to the surface of silica as the respond signal readout. The nanocomposite (BCD@SiO₂@AuNC) was used as a ratiometric fluorescent sensor to realize the selective detection of Gram-negative bacteria. The detection principle was based on the quenching of Cu²⁺ toward AuNCs and the reduction of Gram-negative bacteria toward Cu²⁺. The sensor exhibited good selectivity toward Gram-negative bacteria owing to the copper-homeostasis mechanism possessed by the bacteria. The sensor demonstrated linear response to the logarithm concentration of Gram-negative bacteria with determination coefficients higher than 0.912. The feasibility of the sensor was verified by analysis of Gram-negative bacteria in eggshell, swimming pool water, as well as Chinese cabbage samples with recoveries ranging from 93.9% to 109%.

Nanotechnology for Targeted Detection and Removal of Bacteria: Opportunities and Challenges

The emergence of nanotechnology has created unprecedented hopes for addressing several unmet industrial and clinical issues, including the growing threat so-termed "antibiotic resistance" in medicine. Over the last decade, nanotechnologies have demonstrated promising applications in the identification, discrimination, and removal of a wide range of pathogens. Here, recent insights into the field of bacterial nanotechnology are examined that can substantially improve the fundamental understanding of nanoparticle and bacteria interactions. A wide range of developed nanotechnology-based approaches for bacterial detection and removal together with biofilm eradication are summarized. The challenging effects of nanotechnologies on beneficial bacteria in the human body and environment and the mechanisms of bacterial resistance to nanotherapeutics are also reviewed.

Metal-Ion-Responsive Chromogenic Probe for Rapid, On-Location Detection of Foodborne Bacterial Pathogens in Contaminated Food Items

An amphiphilic chromogenic probe based on an oxidized di(indolyl)arylmethane backbone has been utilized for visual detection of both Cu²⁺ (detection limit = 8.5 ppb) and Hg²⁺ (detection limit = 10.2 ppb) ions via mutually independent sensing pathways. The Cu²⁺ ion binds to the carboxylate ends (donor site) and induces a color change from orange to yellow in the aqueous medium, while coordinating Hg²⁺ at the bisindolyl moiety (acceptor site) can result in the formation of a red-colored solution. Interestingly, by selecting the proper excitation channel, we can specifically excite either the monomer species or nanoaggregates. The addition of Hg²⁺ enhances the monomer fluorescence, while Cu²⁺ induces quenching. However, in both cases, metal-ion coordination triggers dissociation of a preformed self-assembled structure. Further, the in-situ-formed Cu(II) complex was utilized for rapid, on-location detection of food-borne pathogens, such as Escherichia coli (E. coli) in contaminated food items and water (detection limit = 52 CFU·mL^-1). E. coli induces reduction of Cu²⁺ to Cu⁺ and transforms the yellow-colored solution into an orange-colored solution. Finally, low-cost, reusable paper strips were designed as an eco-friendly, sustainable strategy to detect bacterial pathogens.

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.

[Application of carbon dots in analysis and detection of antibiotics]

Antibiotics have been overused in recent years because of their remarkable curative effect, but this has led to considerable environmental pollution. Therefore, the development of approaches aimed at the effective detection and control of the antibiotics is vital for protecting the environment and human health. Many conventional strategies (such as high-performance liquid chromatography (HPLC), gas chromatography (GC), high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS)) are currently in use for the detection of antibiotics. These strategies have aroused a great deal of interest because of their outstanding features of high efficiency and speed, good reproducibility, automation, etc. However, various problems such as tedious sample pretreatment, low detection sensitivity, and high cost must be overcome for the effective detection of antibiotics in environmental samples. Consequently, it is of great significance to improve the detection sensitivity of antibiotics. The development of new materials combined with the existing detection technology has great potential to improve the detection results for antibiotics. Carbon dots (CDs) are a new class of nanomaterials with particle sizes in the range of 0-10 nm. In addition, CDs have desirable properties such as small particle effect, excellent electrical properties, unique optical properties, and good biocompatibility. Hence, they have been widely utilized for the detection of antibiotics in environmental samples. In this review, the application of CDs combined with sensors and chromatographic technology for the detection of antibiotics in the last five years are summarized. The development prospects of CD-based materials and their application to the analysis and detection of antibiotics are presented. In this review, many new sensors (CDs combined with molecularly imprinted polymer sensors, aptamer sensors, electrochemiluminescence sensors, fluorescence sensors, and electrochemical sensors) combined with CD-based materials and their use in the detection of antibiotics are summarized. Furthermore, advanced analysis methods such as ratiometric sensor and array sensor methods are reviewed. The novel analysis methods provide a new direction toward the detection of antibiotics by CDs combined with a sensor. Moreover, CD-based chromatographic stationary phases for the separation of antibiotics are also summarized in this manuscript. It is reported that the detection sensitivity for antibiotics can be greatly improved by the combination of CDs and a sensor. Nevertheless, a literature survey reveals that the detection of antibiotics in complex environmental samples is confronted with numerous challenges, including the fabrication of highly sensitive sensors in combination with CDs. Furthermore, the development of novel high-performance materials is of imperative. In addition, it is important to develop new methods for effective data processing. The separation of antibiotics with CDs as the chromatographic stationary phases is in the preliminary stage, and the separation mechanism remains to be clarified. In conclusion, there are still many problems to be overcome when using CDs as novel materials for the detection of antibiotics in environmental samples. Nowadays, CD-based materials are being intensively studied, and various analytical detection technologies are being rapidly developed. In the future, CD-based materials are expected to play an important role in the detection of antibiotics and other environmental pollutants.

Water-Soluble Blue Fluorescent Nonconjugated Polymer Dots from Hyaluronic Acid and Hydrophobic Amino Acids

Fluorescent polymers have been increasingly investigated to improve their water solubility and biocompatibility to enhance their performance in drug delivery and theranostic applications. However, the environmentally friendly synthesis and dual functionality of such systems remain a challenge due to the complicated synthesis of conventional fluorescent materials. Herein, we generated a novel blue fluorescent polymer dot through chemical conjugation of hydrophobic amino acids to hyaluronic acid (HA) under one-pot green chemistry conditions. These nonconjugated fluorescent polymer dots (NCPDs) are water soluble, nontoxic to cells, have high fluorescence quantum yield, and can be used for in vitro bioimaging. HA-derived NCPDs exhibit excitation wavelength-dependent fluorescent properties. In addition, the NCPDs also show enhanced doxorubicin loading and delivery in naive and drug-resistant breast cancer cells in 2D and 3D tumor cellular systems. These results demonstrate the potential for successful synthetic scale-up and applications for HA-derived NCPDs.

Kaleidoscopic fluorescent arrays for machine-learning-based point-of-care chemical sensing

Multiplexed analysis allows simultaneous measurements of multiple targets, improving the detection sensitivity and accuracy. However, highly multiplexed analysis has been challenging for point-of-care (POC) sensing, which requires a simple, portable, robust, and affordable detection system. In this work, we developed paper-based POC sensing arrays consisting of kaleidoscopic fluorescent compounds. Using an indolizine structure as a fluorescent core skeleton, named Kaleidolizine (KIz), a library of 75 different fluorescent KIz derivatives were designed and synthesized. These KIz derivatives are simultaneously excited by a single ultraviolet (UV) light source and emit diverse fluorescence colors and intensities. For multiplexed POC sensing system, fluorescent compounds array on cellulose paper was prepared and the pattern of fluorescence changes of KIz on array were specific to target chemicals adsorbed on that paper. Furthermore, we developed a machine-learning algorithm for automated, rapid analysis of color and intensity changes of individual sensing arrays. We showed that the paper sensor arrays could differentiate 35 different volatile organic compounds using a smartphone-based handheld detection system. Powered by the custom-developed machine-learning algorithm, we achieved the detection accuracy of 97% in the VOC detection. The highly multiplexed paper sensor could have favorable applications for monitoring a broad-range of environmental toxins, heavy metals, explosives, pathogens.

Full Color Tunable Aggregation-Induced Emission Luminogen for Bioimaging Based on an Indolizine Molecular Framework

By taking advantage of a unique mechanism of aggregation-induced emission (AIE) phenomena, AIE luminogens (AIEgens) have been provided as a solution to overcome the limitations of conventional fluorophores bearing the feature of aggregation-caused quenching (ACQ) phenomena. Especially, AIEgens paved the way to develop fluorogenic probes ideal for fluorescent imaging in live cell conditions. Despite the high demand for discovery of new AIEgens, it is still challenging to find a versatile molecular platform to generate diverse AIEgens. Herein, we report a new colorful molecular framework, Kaleidolizine (KIz), as a molecular platform for AIEgen generation. The KIz system allows systematic tuning of the emission wavelength from 455 to 564 nm via perturbation of the electron density of substituents on the indolizine core. Increasing the water fraction of the KIz solution in the THF/water mixture induces the fluorescence intensity increase up to 120-fold. Crystal structure analysis, computational calculations, and solvatochromism studies suggest that a synergistic effect between the intramolecular charge transfer and restriction of intramolecular rotation acts as the AIE mechanism in the KIz system. Conjugation of the triphenylphosphonium moiety to KIz allows successful development of triphenylphosphonium (TPP)-KIz for real-time bioimaging of innate mitochondria in live cells, thereby revealing the potential of KIz as a versatile molecular platform to generate fluorogenic probes based on AIE phenomena. We do believe the KIz system could serve as a new, reliable, and generally applicable molecular platform to develop various AIEgens having desired photophysical properties along with an excellent signal-to-noise ratio and with experimental convenience especially for fluorogenic live cell imaging.

Recent methods and biosensors for foodborne pathogen detection in fish: progress and future prospects to sustainable aquaculture systems

The aquaculture industry has advanced toward sustainable recirculating systems, in where parameters of food quality are strictly monitored. Despite that, as in the case of conventional aquaculture practices, the recirculating systems also suffer threats from Aeromonas spp., Vibrio spp., Streptococcus spp., among other foodborne pathogens infecting farmed fish. The aquaculture pathogens are routinely detected by conventional PCR methods or antibody-based tests, with the detection protocols confined to laboratory use. Emerging assay technologies and biosensors recently reported in the literature open new opportunities to the development of sensitive, specific, and portable analytical devices to use in the field. Techniques of DNA/RNA analysis, immunoassays and other nanomolecular technologies have been facing important advances in response time, sensitivity, and enhanced power of discrimination among and within species. Moreover, the recent developments of electrochemical and optical signal transduction have facilitated the incorporation of the innovative assays to practical miniaturized devices. In this work, it is provided a critical review over foodborne pathogen detection by existing and promising methods and biosensors applied to fish samples and extended to other food matrices. While isothermal DNA/RNA amplification methods can be highlighted among the assay methods for their promising analytical performance and suitability for point-of-care testing, the electrochemical transduction provides a way to achieve cost-effective biosensors amenable to use in the aquaculture field. The adoption of new methods and biosensors would constitute a step forward in securing sustainable aquaculture systems.

One stone, three birds: one AIEgen with three colors for fast differentiation of three pathogens

Visually identifying pathogens favors rapid diagnosis at the point-of-care testing level. Here, we developed a microenvironment-sensitive aggregation-induced emission luminogen (AIEgen), namely IQ-Cm, for achieving fast discrimination of Gram-negative bacteria, Gram-positive bacteria and fungi by the naked-eye. With a twisted donor-acceptor and multi-rotor structure, IQ-Cm shows twisted intramolecular charge transfer (TICT) and AIE properties with sensitive fluorescence color response to the microenvironment of pathogens. Driven by the intrinsic structural differences of pathogens, IQ-Cm with a cationic isoquinolinium moiety and a membrane-active coumarin unit as the targeting and interacting groups selectively locates in different sites of three pathogens and gives three naked-eye discernible emission colors. Gram-negative bacteria are weak pink, Gram-positive bacteria are orange-red and fungi are bright yellow. Therefore, based on their distinctive fluorescence response, IQ-Cm can directly discriminate the three pathogens at the cell level under a fluorescence microscope. Furthermore, we demonstrated the feasibility of IQ-Cm as a visual probe for fast diagnosis of urinary tract infections, timely monitoring of hospital-acquired infection processes and fast detection of molds in the food field. This simple visualization strategy based on one single AIEgen provides a promising platform for rapid pathogen detection and point-of-care diagnosis.

Fluorescent Sensor Arrays Can Predict and Quantify the Composition of Multicomponent Bacterial Samples

Fast and reliable identification of infectious disease agents is among the most important challenges for the healthcare system. The discrimination of individual components of mixed infections represents a particularly difficult task. In the current study we further expand the functionality of a ratiometric sensor array technology based on small-molecule environmentally-sensitive organic dyes, which can be successfully applied for the analysis of mixed bacterial samples. Using pattern recognition methods and data from pure bacterial species, we demonstrate that this approach can be used to quantify the composition of mixtures, as well as to predict their components with the accuracy of ~80% without the need to acquire additional reference data. The described approach significantly expands the functionality of sensor arrays and provides important insights into data processing for the analysis of other complex samples.

Identification of Catecholamine Neurotransmitters Using a Fluorescent Electronic Tongue

Catecholamine neurotransmitters, specifically, dopamine (DA), epinephrine (EP), and norepinephrine (NE), are known as substantial indicators of various neurological diseases. Developing rapid detection methods capable of simultaneously screening their concentrations is highly desired for early clinical diagnosis of such diseases. To this aim, we have designed an optical sensor array using three fluorescent dyes with distinct emission bands and have monitored variations in their emission profiles upon the addition of DA, EP, and NE in the presence of gold ions. Because of the different reducing power of catecholamines, differently sized gold nanoparticles (GNPs) with different levels of aggregation were generated, resulting in different amounts of spectral overlap between the absorption band of the in situ generated plasmonic GNPs and the emission bands of the fluorescent dyes. These energy-transfer-based fingerprint profiles were used to discriminate the neurotransmitters by applying pattern recognition methods including linear discriminant analysis (LDA) and artificial neural networks (ANN) and to determine their concentration using multiple linear regression (MLR). Our proposed array also showed a good performance in the discrimination of DA, EP, and NE in complex biological media such as human urine.

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.

Conductometric sensor for viable Escherichia coli and Staphylococcus aureus based on magnetic analyte separation via aptamer

A method is described to determine viable populations of Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus). The method employs aptamer-magnetic separation combined with resistivity based detection. The bacteria were separated by means of aptamer-functionalized magnetic beads. They were then quantified by measuring their growth kinetics through time-dependent conductivity changes of culture media. The time-course of growth was logged by real-time and contactless measurements that yielded starting concentrations from the duration of lag intervals prior to the log phase of growth. In pure water samples, the linear ranges for measuring E. coli and S. aureus cells are 2.5 × 10³-2.5 × 10⁸ CFU·mL^-1 and 4.1 × 10³-4.1 × 10⁸ CFU·mL^-1, respectively. In spiked tap water samples, the lower limits of detection are 2.3 × 10⁴ CFU·mL^-1 and 4.0 × 10³ CFU·mL^-1 for E. coli and S. aureus, with recoveries of 87.0-108.7% and 92.5-105.0%, respectively. The relative standard deviation of these measurements (10.0%) is below that of plate counting method (13.9%). The presence of micro/nanoparticles such as magnetic beads or selenium nanoparticles in the culture media does not interfere, unlike in case of automatted optical density monitoring. The E. coli and S. aureus cells captured on the aptamer-functionalized magnetic beads can be directly tested for their susceptibility to antibiotics. The process of magnetic separation and determination of load burden requires neither bulky, sophisticated equipment nor expensive reagents. Graphical abstractAptamer-functionalized magnetic beads are used to selectively capture and separate E. coli and S. aureus cells in aqueous samples. They are directly transferred to a multichannel conductometric sensor for the quantification of viable bacteria via automated monitoring of their growth kinetics.

Recent Advances and Perspectives of Molecularly Imprinted Polymer-Based Fluorescent Sensors in Food and Environment Analysis

Molecular imprinting technology (MIT), also known as molecular template technology, is a new technology involving material chemistry, polymer chemistry, biochemistry, and other multi-disciplinary approaches. This technology is used to realize the unique recognition ability of three-dimensional crosslinked polymers, called the molecularly imprinted polymers (MIPs). MIPs demonstrate a wide range of applicability, good plasticity, stability, and high selectivity, and their internal recognition sites can be selectively combined with template molecules to achieve selective recognition. A molecularly imprinted fluorescence sensor (MIFs) incorporates fluorescent materials (fluorescein or fluorescent nanoparticles) into a molecularly imprinted polymer synthesis system and transforms the binding sites between target molecules and molecularly imprinted materials into readable fluorescence signals. This sensor demonstrates the advantages of high sensitivity and selectivity of fluorescence detection. Molecularly imprinted materials demonstrate considerable research significance and broad application prospects. They are a research hotspot in the field of food and environment safety sensing analysis. In this study, the progress in the construction and application of MIFs was reviewed with emphasis on the preparation principle, detection methods, and molecular recognition mechanism. The applications of MIFs in food and environment safety detection in recent years were summarized, and the research trends and development prospects of MIFs were discussed.

A Capacitive Micromachined Ultrasonic Transducer-Based Resonant Sensor Array for Portable Volatile Organic Compound Detection with Wireless Systems

The development of portable volatile organic compound (VOC) sensors is essential for home healthcare and workplace safety because VOCs are environmental pollutants that may critically affect human health. Here, we report a compact and portable sensor platform based on a capacitive micromachined ultrasonic transducer (CMUT) array offering multiplex detection of various VOCs (toluene, acetone, ethanol, and methanol) using a single read-out system. Three CMUT resonant devices were functionalized with three different layers: (1) phenyl-selective peptide, (2) colloids of single-walled nanotubes and peptide, and (3) poly(styrene-co-allyl alcohol). As each device exhibited different sensitivities to the four VOCs, we performed principal component analysis to achieve selective detection of all four gases. For the simultaneous detection of VOCs using CMUT sensors, the changes in the resonant frequencies of three devices were monitored in real time, but using only a single oscillator through an electrically controlled relay to achieve compactness. In addition, by devising a wireless system, measurement results were transmitted to a smartphone to monitor the concentration of VOCs. We used multiple sensors to obtain a larger number of fingerprints for pattern recognition to enhance selectivity but interfaced these sensors with a single read-out circuit to minimize the footprint of the overall system. The compact CMUT-based sensor array based on a multiplex detection scheme is a promising sensor platform for portable VOC monitoring.

Rapid Identification of Bacteria by Membrane-Responsive Aggregation of a Pyrene Derivative

An imidazolium-derived pyrene aggregation was developed to rapidly identify and quantify different bacteria species. When the nonemissive aggregates bound to the anionic bacteria surface, the sensor disassembled to turn on significant fluorescence. At the same time, ratiometric signals between pyrene monomer and excimer emission were controlled by different interactions with various bacteria surfaces. The resulted different fluorescent emission profiles then were obtained as fingerprints for various bacterial species. By converting emission profiles directly into output signals of two channels, fluorescence increase and ratiometric change, a two-dimensional analysis map was generated for bacteria identification. We demonstrated that our sensor rapidly identified 10 species of bacteria and 14 clinical isolated multidrug-resistant bacteria, and we determined their staining properties (Gram-positive or Gram-negative).

A coumarin–hemicyanine hybrid as a ratiometric fluorescent sensor of microenvironment proticity

ICT-based ratiometric fluorescent probe developed to selectively monitor microenvironment proticity within biopolymer targets with well resolved dual emission channels.

Recent Advances in the Race to Design a Rapid Diagnostic Test for Antimicrobial Resistance

Even with advances in antibiotic therapies, bacterial infections persistently plague society and have amounted to one of the most prevalent issues in healthcare today. Moreover, the improper and excessive administration of antibiotics has led to resistance of many pathogens to prescribed therapies, rendering such antibiotics ineffective against infections. While the identification and detection of bacteria in a patient's sample is critical for point-of-care diagnostics and in a clinical setting, the consequent determination of the correct antibiotic for a patient-tailored therapy is equally crucial. As a result, many recent research efforts have been focused on the development of sensors and systems that correctly guide a physician to the best antibiotic to prescribe for an infection, which can in turn, significantly reduce the instances of antibiotic resistance and the evolution of bacteria "superbugs." This review details the advantages and shortcomings of the recent advances (focusing from 2016 and onward) made in the developments of antimicrobial susceptibility testing (AST) measurements. Detection of antibiotic resistance by genomic AST techniques relies on the prediction of antibiotic resistance via extracted bacterial DNA content, while phenotypic determinations typically track physiological changes in cells and/or populations exposed to antibiotics. Regardless of the method used for AST, factors such as cost, scalability, and assay time need to be weighed into their design. With all of the expansive innovation in the field, which technology and sensing systems demonstrate the potential to detect antimicrobial resistance in a clinical setting?

Probing the self-assembly dynamics and internal structure of amphiphilic hyaluronic acid conjugates by fluorescence spectroscopy and molecular dynamics simulations

Polymeric nanoparticles are increasingly used as biocompatible carriers for drugs and imaging agents. Understanding their self-assembly dynamics and morphology is of ultimate importance to develop nanoformulations with optimal characteristics. To achieve better performance, it is vital to account for cargo-carrier interactions at the molecular level. The self-assembly dynamics were studied and the internal structure of nanoparticles derived from a series of hydrophobically modified hyaluronic acid was revealed. Environment-sensitive ratiometric fluorescent probes provide valuable information about the nanoparticle's interior morphology, and molecular dynamics simulations complement the overall picture with insights into intramolecular and intermolecular interactions of the polymer, as well as its interactions with the small-molecule load. van der Waals and π-π interactions of the hydrophobic side fragments play a leading role in self-assembly and loading of hydrophobic small molecules. Aliphatic substituents form more extensive hydrophobic domains, while aromatic moieties allow more interaction of the loaded small molecules with the surrounding solvent.