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

Integrating optical and electrical sensing with machine learning for advanced particle characterization

Particle classification plays a crucial role in various scientific and technological applications, such as differentiating between bacteria and viruses in healthcare applications or identifying and classifying cancer cells. This technique requires accurate and efficient analysis of particle properties. In this study, we investigated the integration of electrical and optical features through a multimodal approach for particle classification. Machine learning classifier algorithms were applied to evaluate the impact of combining these measurements. Our results demonstrate the superiority of the multimodal approach over analyzing electrical or optical features independently. We achieved an average test accuracy of 94.9% by integrating both modalities, compared to 66.4% for electrical features alone and 90.7% for optical features alone. This highlights the complementary nature of electrical and optical information and its potential for enhancing classification performance. By leveraging electrical sensing and optical imaging techniques, our multimodal approach provides deeper insights into particle properties and offers a more comprehensive understanding of complex biological systems.

High-throughput fluorescence sensing array based on tetraphenylethylene derivatives for detecting and distinguishing pathogenic microbes

Infections induced by pathogenic microorganisms will bring negative effects such as diseases that damage health and result in heavy economic burden. Therefore, it is very important to detect and identify the pathogens in time. Moreover, traditional clinical diagnosis or food testing often faces the problem of dealing with a large number of samples. Here, we designed a high-throughput fluorescent sensor array based on the different binding ability of five tetraphenylethylene derivatives (TPEs) with various side chains to different kinds of pathogenic microbes, which is used to detect and distinguish various species, so as to realize rapid mass diagnosis, and hopefully provide guidance for further determination of microbial infections and clinical treatment.

Immobilization of a broad host range phage on the peroxidase-like Fe-MOF for colorimetric determination of multiple Salmonella enterica strains in food

A broad host range phage-based nanozyme (Fe-MOF@SalmpYZU47) was prepared for colorimetric detection of multiple Salmonella enterica strains. The isolation of a broad host range phage (SalmpYZU47) capable of infecting multiple S. enterica strains was achieved. Then, it was directly immobilized onto the Fe-MOF to prepare Fe-MOF@SalmpYZU47, exhibiting peroxidase-like activity. The peroxidase-like activity can be specifically inhibited by multiple S. enterica strains, benefiting from the broad host range capture ability of Fe-MOF@SalmpYZU47. Based on it, a colorimetric detection approach was developed for S. enterica in the range from 1.0 × 102 to 1.0 × 108 CFU mL-1, achieving a low limit of detection (LOD) of 11 CFU mL-1. The Fe-MOF@SalmpYZU47 was utilized for detecting S. enterica in authentic food samples, achieving recoveries ranging from 91.88 to 105.34%. Hence, our proposed broad host range phage-based nanozyme exhibits significant potential for application in the colorimetric detection of pathogenic bacteria.

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.

Optical sensing for real-time detection of food-borne pathogens in fresh produce using machine learning

Contaminated fresh produce remains a prominent catalyst for food-borne illnesses, prompting the need for swift and precise pathogen detection to mitigate health risks. This paper introduces an innovative strategy for identifying food-borne pathogens in fresh produce samples from local markets and grocery stores, utilizing optical sensing and machine learning. The core of our approach is a photonics-based sensor system, which instantaneously generates optical signals to detect pathogen presence. Machine learning algorithms process the copious sensor data to predict contamination probabilities in real time. Our study reveals compelling results, affirming the efficacy of our method in identifying prevalent food-borne pathogens, including Escherichia coli (E. coli) and Salmonella enteric, across diverse fresh produce samples. The outcomes underline our approach's precision, achieving detection accuracies of up to 95%, surpassing traditional, time-consuming, and less accurate methods. Our method's key advantages encompass real-time capabilities, heightened accuracy, and cost-effectiveness, facilitating its adoption by both food industry stakeholders and regulatory bodies for quality assurance and safety oversight. Implementation holds the potential to elevate food safety and reduce wastage. Our research signifies a substantial stride toward the development of a dependable, real-time food safety monitoring system for fresh produce. Future research endeavors will be dedicated to optimizing system performance, crafting portable field sensors, and broadening pathogen detection capabilities. This novel approach promises substantial enhancements in food safety and public health.

A Method Based on a Modified Fluorescence In Situ Hybridization (FISH) Approach for the Sensing of Staphylococcus aureus from Nasal Samples

Staphylococcus aureus is a major source of bacteremia and develops several complications, causing high morbidity and mortality. Rapid identification and detection of these bacteria have become an important issue for biomedical applications. Herein, an optical method based on a modified fluorescence in situ hybridization (FISH) approach has been established using DNA hybridization technology for the swift detection of pathogenic S. aureus from clinical samples. The platform was constructed with single-stranded genomic DNA and microbial colony by directly immobilizing in agarose-polyvinyl alcohol (AG-PVA) hydrogel on the surface of a glass slide. The probe was based on an elongation factor encoding the tuf gene, which binds with equal affinity to single-stranded DNA targets as well as surface proteins on microbial cells. The probe was labeled with MFP488 fluorophore having excitation wavelength 501 nm. The hybridization of the labeled probe with the target DNA and surface proteins was carried out under optimal FISH conditions, and the detection of bacteria was based on temporary field excitation of the labeled probe under a fluorescence microscope. Positive hybridization signals were detected by high fluorescence intensity. In comparison to genomic DNA, robust signals were observed with microbial cells, perhaps due to the moonlighting effect of the elongation factor Tu (Ef-Tu) expressed on the surface of bacterial cells. The applicability of the developed platform was tested on pediatric nasal samples, and results were verified with real-time qPCR. The designed platform is stable and sensitive, and after detailed optimization, a portable structure for on-site detection of pathogenic bacteria from clinical samples can be produced.

A pomegranate seed-structured nanozyme-based colorimetric immunoassay for highly sensitive and specific biosensing of Staphylococcus aureus

Staphylococcus aureus (S. aureus) infections are a serious threat to human health. The development of rapid and sensitive detection methods for pathogenic bacteria is crucial for accurate drug administration. In this research, by combining the advantages of enzyme-linked immunosorbent assay (ELISA), we synthesized nanozymes with high catalytic performance, namely pomegranate seed-structured bimetallic gold-platinum nanomaterials (Ps-PtAu NPs), which can catalyze a colorless TMB substrate into oxidized TMB (oxTMB) with blue color to achieve colorimetric analysis of S. aureus. Under the optimal conditions, the proposed biosensor could quantitatively detect S. aureus at levels ranging from 1.0 × 101 to 1.0 × 106 CFU mL-1 with a limit of detection (LOD) of 3.9 CFU mL-1. Then, an integrated color picker APP on a smartphone enables on-site point-of-care testing (POCT) of S. aureus with LOD as low as 1 CFU mL-1. Meanwhile, the proposed biosensor is successfully applied to the detection of S. aureus in clinical samples with high sensitivity and specificity.

Functional fluorescent nanomaterials for the detection, diagnosis and control of bacterial infection and biofilm formation: Insight towards mechanistic aspects and advanced applications

Infectious diseases resulting from the high pathogenic potential of several bacteria possesses a major threat to human health and safety. Traditional methods used for screening of these microorganisms face major issues with respect to detection time, selectivity and specificity which may delay treatment for critically ill patients past the optimal time. Thus, a convincing and essential need exists to upgrade the existing methodologies for the fast detection of bacteria. In this context, increasing number of newly emerging nanomaterials (NMs) have been discovered for their effective use and applications in the area of diagnosis in bacterial infections. Recently, functional fluorescent nanomaterials (FNMs) are extensively explored in the field of biomedical research, particularly in developing new diagnostic tools, nanosensors, specific imaging modalities and targeted drug delivery systems for bacterial infection. It is interesting to note that organic fluorophores and fluorescent proteins have played vital role for imaging and sensing technologies for long, however, off lately fluorescent nanomaterials are increasingly replacing these due to the latter's unprecedented fluorescence brightness, stability in the biological environment, high quantum yield along with high sensitivity due to enhanced surface property etc. Again, taking advantage of their photo-excitation property, these can also be used for either photothermal and photodynamic therapy to eradicate bacterial infection and biofilm formation. Here, in this review, we have paid particular attention on summarizing literature reports on FNMs which includes studies detailing fluorescence-based bacterial detection methodologies, antibacterial and antibiofilm applications of the same. It is expected that the present review will attract the attention of the researchers working in this field to develop new engineered FNMs for the comprehensive diagnosis and treatment of bacterial infection and biofilm formation.

Bacterial metabolism-triggered-chemiluminescence-based point-of-care testing platform for sensitive detection and photothermal inactivation of Staphylococcus aureus

Post-operative pathogenic infections in liver transplantation seriously threaten human health. It is essential to develop novel methods for the highly sensitive and rapid detection of Staphylococcus aureus (S. aureus). Interestingly, the combination of the property of bacteria to secrete hydrogen peroxidase, bacterial metabolism-triggered-chemiluminescence (CL)-based bioassays can be as a candidate point-of-care testing (POCT) for the detection of S. aureus against the CL substrate Luminol and hydrogen peroxide without excitation light sources. Here, a CL-based strategy with stable and visualized CL intensity was fabricated according to a hybrid biomimetic enzyme of copper-Hemin metal-organic framework, which enhances the biological enzyme activity while improving the stability and sensitivity of the assay. By further integrating S. aureus-specific capture and one-step separation of the antibody-modified Fe3O4 NPs (Fe3O4 NPs@Ab), the portable device integrated smartphone enables CL-based POCT for specific detection of S. aureus in the range of 101-106 CFU/mL with a limit of detection as low as 1 CFU/mL. Specifically, S. aureus can be eliminated after detection with high antibacterial efficiency due to the excellent photothermal properties of Fe3O4 NPs@Ab. The developed multifunctional platform has the advantages of simplicity of operation and low cost, indicating great potential in clinical applications.

Advances in Microfluidics Techniques for Rapid Detection of Pesticide Residues in Food

Food safety is a significant issue that affects people worldwide and is tied to their lives and health. The issue of pesticide residues in food is just one of many issues related to food safety, which leave residues in crops and are transferred through the food chain to human consumption. Foods contaminated with pesticide residues pose a serious risk to human health, including carcinogenicity, neurotoxicity, and endocrine disruption. Although traditional methods, including gas chromatography, high-performance liquid chromatography, chromatography, and mass spectrometry, can be used to achieve a quantitative analysis of pesticide residues, the disadvantages of these techniques, such as being time-consuming and costly and requiring specialist staff, limit their application. Therefore, there is a need to develop rapid, effective, and sensitive equipment for the quantitative analysis of pesticide residues in food. Microfluidics is rapidly emerging in a number of fields due to its outstanding strengths. This paper summarizes the application of microfluidic techniques to pyrethroid, carbamate, organochlorine, and organophosphate pesticides, as well as to commercial products. Meanwhile, the study also outlines the development of microfluidics in combination with 3D printing technology and nanomaterials for detecting pesticide residues in food.