Method For Detection Of Bacteria Research Articles

Prevalence and Molecular Characterization of Colistin Resistance in Gram-negative Bacteria from Nigeria Hospitals: A Systematic Review

Antibiotic resistance over the years, has emerged as a significant global public health problem, driven by the speedy adaptation of microorganisms to commonly prescribed antibiotics. Colistin, previously regarded as a last-resort antibiotic for treating infections caused by Gram-negative bacteria, is increasingly becoming resistant due to chromosomal alterations and the acquisition of resistance genes carried by plasmids, particularly the mcr genes. The mobile colistin resistance gene (mcr-1) was first discovered in E. coli from China in 2016. Since that time, studies have revealed that different variants of mcr genes ranging from mcr-1 to mcr-10, mainly in Enterobacteriaceae from various parts of the world, which is a focal concern for public health. The co-presence of colistin-resistant genes with other antibiotic resistance determinants further conspire to frustrate treatment strategies and underscores the urgent need for enhanced surveillance and antimicrobial stewardship efforts. Therefore, a good grasp of the mechanisms driving colistin resistance and monitoring its global prevalence are essential steps in addressing the growing threat of antimicrobial resistance and preserving the efficacy of existing antibiotics. This review emphasizes the critical role of colistin as a last-choice antibiotic, elucidates the mechanisms of colistin resistance and the dissemination of resistant genes. It also explores the global prevalence of mcr genes, and evaluates the current detection methods for colistin-resistant bacteria. The objective is to shed light on these key aspects with strategies for combating the growing threat of resistance to antibiotics.

Single-cell Raman spectroscopy for rapid detection of bacteria in ballast water and UV254 treatment evaluation

The increasing global trade has facilitated the transfer of ship ballast water, which has emerged as a primary pathway for alien species invasion into marine ecosystems, posing significant threats to marine biodiversity. Addressing the technical challenges in rapid microorganism detection and treatment efficiency assessment, this study developed a confocal Raman microscopic imaging (CRMI) system integrated with a metal-insulator-metal (MIM) broadband surface-enhanced Raman scattering (SERS) chip, enabling efficient acquisition of single-cell Raman spectroscopy (SCRS). By incorporating machine learning algorithms, the system achieved precise identification of up to 10 bacterial types in ballast water, exhibiting remarkable performance metrics with average accuracy, sensitivity, specificity, and precision above 95.5 %, 95.5 %, 99.5 %, and 95.5 %, respectively. To evaluate the efficacy of ultraviolet (UV) treatment, a Raman spectroscopy-based approach combined with heavy water labeling was introduced to characterize the changes in bacterial single-cell metabolic activity under UV254 irradiation. Experimental results demonstrated that a 10-min UV254 exposure at an effective intensity of 2 mW/cm2 was sufficient to achieve complete bacterial sterilization for the specific ballast water used in our experiment. This study not only established an efficient and accurate method for rapid detection of mixed bacteria but also provided a novel perspective for assessing UV treatment effects. It holds significance and practical value for optimizing ship ballast water management strategies and safeguarding the safety of marine ecosystems.

Rapid detection of Brucella cells using a gold nanoparticle-based aptasensor via a simple colorimetric method

BackgroundBrucellosis is a major worldwide zoonotic disease that is caused by Brucella spp. and threatens the health of communities. Novel methods for rapid detection of Brucella bacteria are beneficial and necessary in preventing infection and subsequent economic losses. Constructing biosensors with nanoparticles is a promising approach for identification of pathogenic bacteria in a short time. This study aimed to introduce a new detection method of Brucella cells using a biosensor, based on gold nanoparticles and a specific aptamer, via a colorimetric reaction. In this work, gold nanoparticles (GNPs) were synthesized and attached to the aptamer through electrostatic bonding. The binding of aptamer to gold nanoparticles was confirmed by Uv/vis spectrophotometry, FT-IR, transmission electron microscope (TEM) and zeta sizer (DLS).ResultsIn the presence of the bacterial cells, aptamers were bound to their targets, and the surfaces of the nanoparticles were depleted from aptamers resulting in intensified peroxidation activity of GNPs, and with the addition of 3, 3′, 5, 5′-tetramethylbenzidine (TMB), the color of the solution was changed from red to purple, which indicated the presence of Brucella. The sensitivity of the aptasensor was investigated using different concentrations of Brucella cells and its specificity was confirmed against several species of bacteria. The results showed that the designed aptasensor was more sensitive compared to PCR assay method with the ability to detect 1.5 × 101 CFU/mL of the bacterial cells.ConclusionThese findings indicate that the designed aptasensor can be used as a simple and rapid diagnostic tool to detect Brucella cells without need to experts and expensive laboratory equipment.

Establishment of a multiplex qPCR method for sensitive detection of proteolytic psychrotrophic bacteria in raw milk

Initial microbiological species and quantity of raw milk significantly affect dairy product quality. In particular, some psychrotrophic bacteria in raw milk can produce heat-stable hydrolases that reduce the stability of dairy products during their shelf life. The purpose of this study was to establish a multiplex real-time fluorescence quantitative polymerase chain reaction (qPCR) rapid detection method for Pseudomonas fluorescens and Lactococcus lactis subsp. lactis, which generally produce protease in raw milk. The primers and probes with good specificity, universality and high sensitivity to the target bacteria were screened by ordinary PCR and qPCR experiments. The quantitative linear relationship and sensitivity of the method for detecting pure DNA and artificially contaminated simulated milk samples were verified. The results showed that the limit of detection (LOD) of this method for pure DNA could reach 3.16 × 10−5 ng/μL. The detection of artificially contaminated samples showed that the LOD for P. fluorescens and L. lactis subsp. lactis could reach 250 and 22 CFU/mL, respectively. The multiplex qPCR method established in this study has good specificity and high sensitivity, which can be used to rapidly detect psychrotrophic bacteria in raw milk. It provides an effective reference strategy for the dairy industry to ensure the microbiological quality of raw milk from the source.

A colorimetric biosensor with infrared sterilization based on CuSe nanoparticles for the detection of E. coli O157:H7 in food samples.

Escherichia coli O157:H7 is a major threat to public health. At present, the detection methods for E. coli O157:H7 mainly include traditional bacterial culture, immunology (enzyme-linked immune-sorbent assay) and molecular biology techniques (polymerase chain reaction). These methods have the limitations of professional operation, waste of time and energy, and high cost. Therefore, we have developed a simple, fast, bactericidal colorimetric biosensor to detect E. coli. O157:H7. The entire process was completed in 80 minutes. The method has been successfully applied to milk and mineral water samples with satisfactory results, proving that the method is an effective method for real-time detection and inactivation of bacteria.

Multispectral pathogens detection in food using multiplex hyperbranched saltatory rolling circle amplification

Foodborne illnesses caused by Salmonella and Staphylococcus aureus are a significant public health concern, leading to societal and economic repercussions. It is important to develop a simple and straightforward bacteria detection and identification method. A triple-probe multiplex rolling circle amplification technique has been developed to simultaneously detect Salmonella Typhimurium and S. aureus. This method utilizes fluorophore-labeled long padlock probes targeting S. Typhimurium invA and S. aureus glnA specific genes, along with a pH-based detection approach for direct visual identification. The multiplex hyperbranched saltatory rolling circle amplification assay at 30 °C has showed promising results with synthetic targets within 30 min and real bacteria within 2 h after establishing the detection settings. The assay is specific for S. aureus and S. Typhimurium, with a limit of detection of 39 μM for fluorescence and 78 μM for colorimetric. In the simulative test of this method for the detection of S. Typhimurium and S. aureus in milk, the limit of detection for the fluorescence signal after 2 h of amplification was 10 CFU/mL and 5 CFU/mL, respectively. The detection method was evaluated to be stable enough to detect pathogen for 3.29 months. Consequently, this triple-probe-multiplex rolling circle amplification method displays notable specificity, sensitivity, as well as ease of interpretation when testing food samples for harmful pathogens.

Monitoring of enteropathogenic Gram-negative bacteria in wastewater treatment plants: a multimethod approach

The wastewater treatment processes are associated with the emission of microbial aerosols, including enteropathogenic bacteria. Their presence in this work environment poses a real threat to the health of employees, both through the possibility of direct inhalation of the contaminated air and indirectly through the pollution of all types of surfaces with such bioaerosol particles. This study aimed to investigate the prevalence of enteropathogenic bacteria in the air, on surfaces, and in wastewater samples collected in four wastewater treatment plants (WWTPs). The effectiveness of conventional culture-biochemical, as well as spectrometric and molecular methods for the rapid detection of enteropathogenic bacteria at workstations related to particular stages of wastewater processing, was also evaluated. Bioaerosol, surface swab, and influent and effluent samples were collected from wastewater plants employing mechanical–biological treatment technologies. The air samples were collected using MAS-100 NT impactor placed at a height of 1.5 m above the floor or ground, simulating aspiration from the human breathing zone. Surface samples were collected with sterile swabs from different surfaces (valves, handles, handrails, and coveyor belts) at workplaces. The raw influent and treated effluent wastewater samples were aseptically collected using sterile bottles. The identification of bacterial entheropathogens was simultaneously conducted using a culture-based method supplemented with biochemical (API) tests, mass-spectrometry (MALDI TOF MS), and molecular (multiplex real-time PCR) methods. This study confirmed the common presence of bacterial pathogens (including enteropathogenic and enterotoxigenic Escherichia coli, Salmonella spp., Campylobacter spp., and Yersinia enterocolitica) in all air, surface, and wastewater samples at studied workplaces. Higher concentrations of enteropathogenic bacteria were observed in the air and on surfaces at workplaces where treatment processes were not hermetized. The results of this study underline that identification of enteropathogenic bacteria in WWTPs is of great importance for the correct risk assessment at workplaces. From the analytical point of view, the control of enteropathogenic bacterial air and surface pollution using rapid multiplex-PCR method should be routinely performed as a part of hygienic quality assessment in WWTPs.

Application of Metagenomic Next-Generation Sequencing in the Diagnosis of Infectious Keratitis.

To determine the advantages of next-generation metagenomic sequencing (mNGS) technology in the diagnosis and treatment of infectious keratitis (IK). A total of 287 patients with IK admitted to the Department of Ophthalmology of Nanjing First Hospital between August 2018 and December 2022 were analyzed retrospectively, and the pathogenic causes, etiological characteristics, detection, treatment methods, and efficacy were summarized. Trauma and foreign matter were the most common causes of IK (144 patients, 50.2%). Of the 287 patients, 228 (79.4%) were diagnosed with a specific etiology, including 110 (48.2%) fungal infections, 44 (19.3%) viral infections, 42 (18.4%) mixed infections, and 30 (13.2%) bacterial infections. Filamentous fungi represented by Fusarium and Aspergillus were the most common, followed by bacteria such as Pseudomonas aeruginosa, Streptococcus pneumoniae, viruses (Herpes Simplex Virus/Varicella-Zoster Virus), and parasites. The positivity rates of secretion culture, corneal laser confocal microscopy (CM), mNGS, and pathological sections were 47.3% (133/281), 45.3% (111/245), 83.9% (104/124), and 19.3% (40/207), respectively. The positivity rate of mNGS for bacteria and viruses was higher than that of the other methods, and the positivity rate for fungi was the same as that for CM. As a result, 214 cases (74.6%) were cured, 51 cases (17.8%) improved, 8 cases (2.8%) did not heal, ocular content enucleation was performed in 14 cases (4.9%), and the overall efficacy rate was 92.3%. Trauma and foreign matter are the main causes of IK. The mNGS technology is an efficient and comprehensive detection method for viruses and bacteria, especially for mixed infections.

Establishment of a Multiplex Detection Method for Common Bacteria in Blood Based on Human Mannan-Binding Lectin Protein-Conjugated Magnetic Bead Enrichment Combined with Recombinase-Aided PCR Technology

ObjectiveRecombinase-aided polymerase chain reaction (RAP) is a sensitive, single-tube, two-stage nucleic acid amplification method. This study aimed to develop an assay that can be used for the early diagnosis of three types of bacteremia caused by Staphylococcus aureus (SA), Pseudomonas aeruginosa (PA), and Acinetobacter baumannii (AB) in the bloodstream based on recombinant human mannan-binding lectin protein (M1 protein)-conjugated magnetic bead (M1 bead) enrichment of pathogens combined with RAP. MethodsRecombinant plasmids were used to evaluate the assay sensitivity. Common blood influenza bacteria were used for the specific detection. Simulated and clinical plasma samples were enriched with M1 beads and then subjected to multiple recombinase-aided PCR (M-RAP) and quantitative PCR (qPCR) assays. Kappa analysis was used to evaluate the consistency between the two assays. ResultsThe M-RAP method had sensitivity rates of 1, 10, and 1 copies/μL for the detection of SA, PA, and AB plasmids, respectively, without cross-reaction to other bacterial species. The M-RAP assay obtained results for < 10 CFU/mL pathogens in the blood within 4 h, with higher sensitivity than qPCR. M-RAP and qPCR for SA, PA, and AB yielded Kappa values of 0.839, 0.815, and 0.856, respectively (P < 0.05). ConclusionAn M-RAP assay for SA, PA, and AB in blood samples utilizing M1 bead enrichment has been developed and can be potentially used for the early detection of bacteremia.

Point-of-Care Diagnostic System for Viable Salmonella Species via Improved Propidium Monoazide and Recombinase Polymerase Amplification Based Nucleic Acid Lateral Flow.

Salmonella species are prominent foodborne microbial pathogens transmitted through contaminated food or water and pose a significant threat to human health. Accurate and rapid point-of-care (POC) diagnosis is gaining attention in effectively preventing outbreaks of foodborne disease. However, the presence of dead bacteria can interfere with an accurate diagnosis, necessitating the development of methods for the rapid, simple, and efficient detection of viable bacteria only. Herein, we used an improved propidium monoazide (PMAxx) to develop a nucleic acid lateral flow (NALF) assay based on recombinase polymerase amplification (RPA) to differentiate viable Salmonella Typhimurium. We selected an RPA primer set targeting the invA gene and designed a probe for NALF. RPA-based NALF was optimized for temperature (30-43 °C), time (1-25 min), and endonuclease IV concentration (0.025-0.15 unit/µL). PMAxx successfully eliminated false-positive results from dead S. Typhimurium, enabling the accurate detection of viable S. Typhimurium with a detection limit of 1.11 × 102 CFU/mL in pure culture. The developed method was evaluated with spiked raw chicken breast and milk with analysis completed within 25 min at 39 °C. This study has potential as a tool for the POC diagnostics of viable foodborne pathogens with high specificity, sensitivity, rapidity, and cost-effectiveness.

A Review on Colistin Resistance: An Antibiotic of Last Resort.

Antibiotic resistance has emerged as a significant global public health issue, driven by the rapid adaptation of microorganisms to commonly prescribed antibiotics. Colistin, previously regarded as a last-resort antibiotic for treating infections caused by Gram-negative bacteria, is increasingly becoming resistant due to chromosomal mutations and the acquisition of resistance genes carried by plasmids, particularly the mcr genes. The mobile colistin resistance gene (mcr-1) was first discovered in E. coli from China in 2016. Since that time, studies have reported different variants of mcr genes ranging from mcr-1 to mcr-10, mainly in Enterobacteriaceae from various parts of the world, which is a major concern for public health. The co-presence of colistin-resistant genes with other antibiotic resistance determinants further complicates treatment strategies and underscores the urgent need for enhanced surveillance and antimicrobial stewardship efforts. Therefore, understanding the mechanisms driving colistin resistance and monitoring its global prevalence are essential steps in addressing the growing threat of antimicrobial resistance and preserving the efficacy of existing antibiotics. This review underscores the critical role of colistin as a last-choice antibiotic, elucidates the mechanisms of colistin resistance and the dissemination of resistant genes, explores the global prevalence of mcr genes, and evaluates the current detection methods for colistin-resistant bacteria. The objective is to shed light on these key aspects with strategies for combating the growing threat of resistance to antibiotics.

Simultaneous Dual-Gene Test of Methicillin-Resistant Staphylococcus Aureus using an Argonaute-Centered Portable and Visual Biosensor.

The development of novel method for drug-resistant bacteria detection is imperative. A simultaneous dual-gene Test of methicillin-resistant Staphylococcus aureus (MRSA) is developed using an Argonaute-centered portable biosensor (STAR). This is the first report concerning Argonaute-based pathogenic bacteria detection. Simply, the species-specific mecA and nuc gene are isothermally amplified using loop-mediated isothermal amplification (LAMP) technique, followed by Argonaute-based detection enabled by its programmable, guided, sequence-specific recognition and cleavage. With the strategy, the targeted nucleic acid signals gene are dexterously converted into fluorescent signals. STAR is capable of detecting the nuc gene and mecA gene simultaneously in a single reaction. The limit of detection is 10 CFU/mL with a dynamic range from 10 to 107 CFU/mL. The sample-to-result time is <65min. This method is successfully adapted to detect clinical samples, contaminated foods, and MRSA-infected animals. This work broadens the reach of Argonaute-based biosensing and presents a novel bacterial point-of-need (PON) detection platform.

Comparison of tet(X4)-containing contigs assembled from metagenomic sequencing data with plasmid sequences of isolates from a cohort of healthy subjects.

Recently discovered tet(X) gene variants have provided new insights into microbial antibiotic resistance mechanisms and their potential consequences for public health. This study focused on detection, analysis, and characterization of Tet(X4)-positive Enterobacterales from the gut microbiota of a healthy cohort of individuals in Singapore using cultivation-dependent and cultivation-independent approaches. Twelve Tet(X4)-positive Enterobacterales strains that were previously obtained from the cohort were fully genome-sequenced and comparatively analyzed. A metagenomic sequencing (MS) data set of the same samples was mined for contigs that harbored the tet(X4) resistance gene. The sequences of tet(X4)-containing contigs and plasmids sequences were compared. The presence of the resistance genes floR and estT (previously annotated as catD) was detected in the same cassette in 10 and 12 out of the 12 tet(X4)-carrying plasmids, respectively. MS detected tet(X4)-containing contigs in 2 out of the 109 subjects, while cultivation-dependent analysis previously reported a prevalence of 10.1%. The tet(X4)-containing sequences assembled from MS data are relatively short (~14 to 33 kb) but show high similarity to the respective plasmid sequences of the isolates. Our findings show that MS can complement efforts in the surveillance of antibiotic resistance genes for clinical samples, while it has a lower sensitivity than a cultivation-based method when the target organism has a low abundance. Further optimization is required if MS is to be utilized in antibiotic resistance surveillance.IMPORTANCEThe global rise in antibiotic resistance makes it necessary to develop and apply new approaches to detect and monitor the prevalence of antibiotic resistance genes in human populations. In this regard, of particular interest are resistances against last-resort antibiotics, such as tigecycline. In this study, we show that metagenomic sequencing can help to detect high abundance of the tigecycline resistance gene tet(X4) in fecal samples from a cohort of healthy human subjects. However, cultivation-based approaches currently remain the most reliable and cost-effective method for detection of antibiotic-resistant bacteria.

Method for detection of pathogenic bacteria from indoor air microbiome samples using high-throughput amplicon sequencing

The exposure of the air microbiome in indoor air posed a detrimental health effect to the building occupants compared to the outdoor air. Indoor air in hospitals has been identified as a reservoir for various pathogenic microbes. The conventional culture-dependent method has been widely used to access the microbial community in the air. However, it has limited capability in enumerating the complex air microbiome communities, as some of the air microbiomes are uncultivable, slow-growers, and require specific media for cultivation. Here, we utilized a culture-independent method via amplicon sequencing to target the V3 region of 16S rRNA from the pool of total genomic DNA extracted from the dust samples taken from hospital interiors. This method will help occupational health practitioners, researchers, and health authorities to efficiently and comprehensively monitor the presence of harmful air microbiome thus take appropriate action in controlling and minimizing the health risks to the hospital occupants. Key features;•Culture-independent methods offer fast, comprehensive, and unbias profiles of pathogenic and non-pathogenic bacteria from the air microbiomes.•Unlike the culture-dependent method, amplicon sequencing allows bacteria identification to the lowest taxonomy levels.

Multiplex Aptamer-Based Fluorescence Assay Using Magnetism-Encoded Nanoparticles for Simultaneous Detection of Multiple Pathogenic Bacteria.

Multiplex assay has emerged as a robust and versatile method for the simultaneous detection of multiple analytes in a single test. However, challenges in terms of poor accuracy and complexity remained. In this work, we developed a multiplex aptamer-based fluorescence assay using magnetism-encoded nanoparticles for the simultaneous detection of multiple pathogenic bacteria. The encapsulation of different amounts of Fe3O4 nanoparticles in zeolitic imidazolate framework-90 (ZIF-90) leads to the formation of Fe3O4@ZIF-90 (FZ) composites with distinct magnetism strengths. By functionalizing a specific aptamer on the surface of the FZ composites, target bacteria can be specifically and precisely separated from a mixed sample in a sequential manner. This property allows for the simultaneous quantitative analysis of multiple target bacteria by using a single-color fluorescence label, thereby resulting in minimal spectral crosstalk interference and improved accuracy. The successful determination of multiple bacteria in contaminated milk samples demonstrates the applicability of this multiplex assay in complex biological matrices. Compared to conventional multiplex fluorescence assays, this approach offers distinct advantages of simplicity, efficiency, and implementation. We believe that this study can provide valuable insights into the development of the multiplex assay while introducing a new method for the simultaneous detection of multiple bacteria.

Rapid identification of bacteria in water by multi-wavelength transmittance spectroscopy and the artificial neural network

Background: Multi-wavelength transmittance spectroscopy, in combination with the artificial neural network, has been a novel tool used to identify and classify microorganisms in recent years.Methods: In our work, the transmittance spectra in the region from 200 to 900 nm for four bacterial species of interest, Escherichia coli (E. coli), Staphylococcus aureus (S. aureus), Klebsiella pneumoniae (K.pneumoniae), and Salmonella typhimurium (S. typhi), were recorded using an ultraviolet–visible spectrophotometer. Considering too much redundant data on the full-wave band spectra, the characteristic wavelength variables were selected using the competitive adaptive reweighting sampling (CARS) algorithm. Spectra of the initial training set of these targeted microorganisms were used to create identification models representing the spectral variability of each species using four kinds of neural networks, namely, backpropagation (BP), radial basis function network (RBF), generalized regression neural network (GRNN), and probabilistic neural network (PNN).Results: The blinded isolate spectra of targeted species were identified using the four identification models given above. Compared to fullband modeling, after using CARS to screen the wavelength variables, four identification models are established for the 35 preferred characteristic wavelengths, and the prediction performance of the four models is notably improved. Among them, the CARS–PNN model is the best, and the identification rates of all targeted bacteria were achieved with 100% accuracy; the calculation time is just approximately 0.04 s.Discussion: The use of CARS can effectively remove useless information from the spectra, reduce model complexity, and enhance model prediction performance. Multi-wavelength transmission spectroscopy, combined with the CARS–PNN method, can provide a new method for the rapid detection of bacteria in water and could be readily extended for bacterial microbiological detection in blood and food.

Investigating enzyme kinetics and fluorescence sensing strategy of CRISPR/Cas12a for foodborne pathogenic bacteria

Foodborne pathogenic bacteria are widespread in various foods, whose cross-contamination and re-contamination are critical influences on food safety. Rapid, accurate, and sensitive detection of foodborne pathogenic bacteria remains a topic of concern. CRISPR/Cas12a can recognize double-stranded DNA directly, showing great potential in nucleic acid detection. However, few studies have investigated the cleavage properties of CRISPR/Cas12a. In this study, the trans-cleavage properties of LbCas12a and AsCas12a were investigated to construct the detection methods for foodborne pathogenic bacteria. The highly sensitive fluorescent strategies for foodborne pathogens were constructed by analyzing the cleavage rates and properties of substrates at different substrate concentrations. Cas12a was activated in the presence of foodborne pathogenic target sequence was present, resulting in the cleavage of a single-stranded reporter ssDNA co-labelled by fluorescein quencher and fluorescein. The sensitivity and specificity of the Cas12a fluorescent strategy was investigated with Salmonella and Staphylococcus aureus as examples. The results showed that AsCas12a was slightly more capable of trans-cleavage than LbCas12a. The detection limits of AsCas12a for Salmonella and Staphylococcus aureus were 24.9 CFU mL−1 and 1.50 CFU mL−1, respectively. In all the seven bacteria, Staphylococcus aureus and Salmonella were accurately discriminated. The study provided a basis for constructing and improving the CRISPR/Cas12a fluorescence strategies. The AsCas12a-based detection strategy is expected to be a promising method for field detection.

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.

Application of the Peroxidase‒like Activity of Nanomaterials for the Detection of Pathogenic Bacteria and Viruses.

Infectious diseases caused by pathogenic bacteria and viruses pose a significant threat to human life and well-being. The prompt identification of these pathogens, characterized by speed, accuracy, and efficiency, not only aids in the timely screening of infected individuals and the prevention of further transmission, but also facilitates the precise diagnosis and treatment of patients. Direct smear microscopy, microbial culture, nucleic acid-based polymerase chain reaction (PCR), and enzyme-linked immunosorbent assay (ELISA) based on microbial surface antigens or human serum antibodies, have made substantial contributions to the prevention and management of infectious diseases. Due to its shorter processing time, simple equipment requirements, and no need for professional and technical personnel, ELISA has inherent advantages over other methods for detecting pathogenic bacteria and viruses. Horseradish peroxidase mediated catalysis of substrate coloration is the key for the detection of target substances in ELISA. However, the variability, high cost, and environmental susceptibility of natural peroxidase greatly limit the application of ELISA in pathogen detection. Compared with natural enzymes, nanomaterials with enzyme-mimicking activity are inexpensive, highly environmentally stable, easy to store and mass producing, etc. Based on their peroxidase-like activities and unique physicochemical properties, nanomaterials can greatly improve the efficiency and ease of use of ELISA-like detection methods for pathogenic bacteria and viruses. This review introduces recent advances in the application of nanomaterials with peroxidase-like activity for the detection of pathogenic bacteria (both gram-negative bacteria and gram-positive bacteria) and viruses (both RNA viruses and DNA viruses). The emphasis is on the detection principle and the evaluation of effectiveness. The limitations and prospects for future translations are also discussed.

Bayesian Statistical Analysis for Bacterial Detection in Pulmonary Endomicroscopic Fluorescence Lifetime Imaging.

Pneumonia, a respiratory disease often caused by bacterial infection in the distal lung, requires rapid and accurate identification, especially in settings such as critical care. Initiating or de-escalating antimicrobials should ideally be guided by the quantification of pathogenic bacteria for effective treatment. Optical endomicroscopy is an emerging technology with the potential to expedite bacterial detection in the distal lung by enabling in vivo and in situ optical tissue characterisation. With advancements in detector technology, optical endomicroscopy can utilize fluorescence lifetime imaging (FLIM) to help detect events that were previously challenging or impossible to identify using fluorescence intensity imaging. In this paper, we propose an iterative Bayesian approach for bacterial detection in FLIM. We model the FLIM image as a linear combination of background intensity, Gaussian noise, and additive outliers (labelled bacteria). While previous bacteria detection methods model anomalous pixels as bacteria, here the FLIM outliers are modelled as circularly symmetric Gaussian-shaped objects, based on their discrete shape observed through visual analysis and the physical nature of the imaging modality. A Hierarchical Bayesian model is used to solve the bacterial detection problem where prior distributions are assigned to unknown parameters. A Metropolis-Hastings within Gibbs sampler draws samples from the posterior distribution. The proposed method's detection performance is initially measured using synthetic images, and shows significant improvement over existing approaches. Further analysis is conducted on real optical endomicroscopy FLIM images annotated by trained personnel. The experiments show the proposed approach outperforms existing methods by a margin of +16.85% ( F1 ) for detection accuracy.