Detection Of Bacteria Research Articles

Sensitive and on-Site Detection of Staphylococcus aureus Based on CRISPR/Cas 13a-Assisted Chemiluminescence Resonance Energy Transfer.

Developing a specific, sensitive, rapid, and on-site method for detecting pathogenic bacteria in food samples is critical to ensuring public safety. This article demonstrates a CRISPR/Cas13a system and a chemiluminescence resonance energy transfer (CRET) (CRISPR/Cas 13a-assisted CRET)-based strategy for sensitive and on-site detection of pathogenic bacteria in real samples. Once the hybrid double strand of aptamerS.aureus-cRNA recognizes the target model bacteria of Staphylococcus aureus (S. aureus), the released cRNA would bind with CRISPR/Cas 13a to form a complex of cRNA-CRISPR/Cas 13a, which could cleave the RNA molecule in the detecting probe of horseradish peroxidase (HRP) modified-gold nanoparticles (AuNPs) linked by RNA (AuNPs-RNA-HRP), resulting in an enhanced chemiluminescence signal due to the CRET "OFF" phenomenon after introducing the chemiluminescence substrate of luminol. The CRISPR/Cas 13a-assisted CRET strategy successfully detected S. aureus in drinking water and milk with detection limits of 20 and 30 cfu/mL, respectively, within the recovery of 90.07-105.50%. Furthermore, after integrating with an immunochromatographic test strip (ICTS), the CRISPR/Cas 13a-assisted CRET strategy achieved the on-site detection of as low as 102 cfu/mL of S. aureus in drinking water and milk via a smartphone, which is about 10 times lower than that in the previously reported AuNPs-based colorimetric ICTS, demonstrating a convenient and sensitive detection method for S. aureus in real samples.

Surface-Enhanced Raman Spectroscopy Sensor Integrated with Ag@ZIF-8@Au Core-Shell-Shell Nanowire Membrane for Enrichment, Ultrasensitive Detection, and Inactivation of Bacteria in the Environment.

A core-shell-shell sandwich material is developed with silver nanowires as the core, ZIF-8 as an inner shell, and gold nanoparticles as the outer shell, namely, Ag@ZIF-8@Au nanowires (AZA-NW). Then, the synthesized AZA-NW is transformed into a surface-enhanced Raman spectroscopy (SERS) sensor (named M-AZA) by the vacuum filtration method and used to enrich, detect, and inactivate traces of bacteria in the environment. The M-AZA sensor has three main functions: (1) trace bacteria are effectively enriched, with an enrichment efficiency of 91.4%; (2) ultrasensitive detection of trace bacteria is realized, with a minimum detectable concentration of 1 × 101 CFU/mL; (3) bacteria are effectively killed up to 92.4%. The shell thickness of ZIF-8 (5-75 nm) is controlled by adjusting the synthesis conditions. At an optimum shell thickness of 15 nm, the effect of gold nanoparticles and ZIF-8 shell on the sensor's stability, SERS activity, and antibacterial performance is investigated. The simulation of the SERS sensor using the finite difference time domain (FDTD) method is consistent with the experimental results, theoretically demonstrating the role of the gold nanoparticles and the ZIF-8 shell. The sensor also shows excellent stability, safety, and generalizability. The campus water sample is then tested on-site by the M-AZA SERS sensor, indicating its potential for practical applications.

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 1.5m 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.

Development of a score model to predict long-term prognosis after community-onset pneumonia in older patients.

The identification of factors associated with long-term prognosis after community-onset pneumonia in elderly patients should be considered when initiating advance care planning (ACP). We aimed to identify these factors and develop a prediction score model. Patients aged 65 years and older, who were hospitalized for pneumonia at nine collaborating institutions, were included. The prognosis of patients 180 days after the completion of antimicrobial treatment for pneumonia was prospectively collected. The total number of analysable cases was 399, excluding 7 outliers and 42 cases with missing data or unknown prognosis. These cases were randomly divided in an 8:2 ratio for score development and testing. The median age was 82 years, and there were 68 (17%) deaths. A multivariate analysis showed that significant factors were performance status (PS) ≥2 (Odds ratio [OR], 11.78), hypoalbuminemia ≤2.5 g/dL (OR, 5.28) and dementia (OR, 3.15), while age and detection of antimicrobial-resistant bacteria were not associated with prognosis. A scoring model was then developed with PS ≥2, Alb ≤2.5, and dementia providing scores of 2, 1 and 1 each, respectively, for a total of 4. The area under the curve was 0.8504, and the sensitivity and specificity were 94.6% and 61.7% at the cutoff of 2, respectively. In the test cases, the sensitivity and specificity were 91.7% and 63.1%, respectively, at a cutoff value of 2. Patients meeting this score should be considered near the end of life, and the initiation of ACP practices should be considered.

Rapid detection of virulence-related genes by multiplex PCR in five pathogenic bacteria of mulberry bacterial wilt

Mulberry bacterial wilt is a devastating disease that is difficult to control and causes serious economic losses to the sericulture industry. This disease is mostly caused by a diverse group of pathogenic and opportunistic bacteria including, Ralstonia pseudosolanacearum, Pantoea ananatis, Enterobacter cloacae complex (ECC), Klebsiella pneumoniae species complex (KpSC), and K. oxytoca complex (KoC). Due to the lack of a rapid and reliable test to simultaneously detect these complex pathogens of mulberry wilt, we developed a multiplex PCR (mPCR) assay to detect five virulence-related genes carried by the pathogenic bacteria of mulberry bacterial wilt disease. The primers were designed for the virulence-related genes: pleD (GGDF structural domain-containing protein), yjfP (esterase), pelY (peripheral pectate lyase), ampD (N-acetyl-anhydromuranmyl-L-alanine amidase), and ripW (type III effector). Overall, the developed mPCR assay showed highly specific, sensitive and reproducible detection of target pathogens. Briefly, the results showed that the mPCR was highly specific in individual reactions, and the lowest detection concentration of the five pathogenic bacteria was 1.87 × 103 CFU/mL (DNA = 2.45 pg/μL). From 46 natural mulberry wilt samples, the mPCR detection rates of P. ananatis, ECC, KpSC, KoC and R. pseudosolanacearum were 8.69, 91.3, 34.7, 23.9 and 65.21%, respectively. The traditional culture media isolation methods showed comparable results. The pathogenicity test of 84 suspected pathogenic bacteria revealed that the morbidity (average morbidity level) caused by the pathogenic bacteria detected by mPCR was ≥ 65.5%, while the morbidity of the undetected pathogenic bacteria was ≤ 35.5%. Based on these results, we believe that the mPCR developed in the present study will be useful in rapid, reproducible, and sensitive detection of the pathogenic bacteria causing mulberry bacterial wilt including, R. pseudosolanacearum, P. ananatis, ECC, KpSC, and KoC.Graphical abstract

Rapid Concentration and Detection of Bacteria in Milk Using a Microfluidic Surface Acoustic Wave Activated Nanosieve.

Rapid detection of microbes is a key feature for monitoring food quality. Unfortunately, current detection systems rely on labor-intensive and time-consuming lab-based processes that are not suitable for point-of-interest applications and typically require several days before results are available. Here, we demonstrate a microfluidic system capable of rapidly concentrating, fluorescent staining, and detecting bacteria in unprocessed complex biological media such as milk. This concentration is done using a surface acoustic wave-driven microfluidic device which operates based on the Bjerknes force, a force generated on one particle by another in its close proximity. We exploit this effect by exciting a tightly packed bed of 50 μm polystyrene microparticles temporarily with surface acoustic waves within a microfluidic device to capture and release bacterial cells on demand. The bacterial cells are fluorescently stained during capture and then detected using fluorescence microscopy upon release. This device offers a high capturing efficiency (>80%) and a 34 Colony Forming Units (CFU)/mL limit of detection, which is 1 order of magnitude below that of plate counting at 30 CFU per standard 100 μL plate (or 300 CFU/mL). This can be attained in just 1 h of processing at 10 μL/min. With this system, we demonstrate that bacterial detection from extremely low concentration samples down to the order of ∼10 CFU/mL is possible without requiring any additional external pre- or postprocessing.

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

Abroad 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 × 108CFUmL-1, achieving a low limit of detection (LOD) of11CFUmL-1. TheFe-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.

PrimerEvalPy: a tool for in-silico evaluation of primers for targeting the microbiome

BackgroundThe selection of primer pairs in sequencing-based research can greatly influence the results, highlighting the need for a tool capable of analysing their performance in-silico prior to the sequencing process. We therefore propose PrimerEvalPy, a Python-based package designed to test the performance of any primer or primer pair against any sequencing database. The package calculates a coverage metric and returns the amplicon sequences found, along with information such as their average start and end positions. It also allows the analysis of coverage for different taxonomic levels.ResultsAs a case study, PrimerEvalPy was used to test the most commonly used primers in the literature against two oral 16S rRNA gene databases containing bacteria and archaea. The results showed that the most commonly used primer pairs in the oral cavity did not match those with the highest coverage. The best performing primer pairs were found for the detection of oral bacteria and archaea.ConclusionsThis demonstrates the importance of a coverage analysis tool such as PrimerEvalPy to find the best primer pairs for specific niches. The software is available under the MIT licence at https://gitlab.citius.usc.es/lara.vazquez/PrimerEvalPy.

Quantitative Analysis of Bifidobacterium and Scardovia wiggsiae in Dental Plaque from Children in Northern Thailand and Their Association with Caries Factors

Abstract Objectives The aim of this study were to measurably detect Bifidobacterium and Scardovia wiggsiae in plaque from severe early childhood caries (S-ECC) and caries-free children and to analyze the interrelation between these bacteria and clinical caries presentation and caries-related factors assessed by questionnaire. Materials and Methods One-hundred forty supra gingiva plaque samples from children aged between 2 and 5 years were used in this study. There were 70 children in each group. Recorded plaque index, modified gingival index, and decay, missing, and filled tooth (dmft) scores. Parents' attitudes, child's oral hygiene, and diet were assessed by questionnaire. DNA was extracted from plaque samples and quantitative real-time polymerase chain reaction using fluorescent dye was performed. Results Plaque (p < 0.001) and modified gingival indices (p < 0.001) in the S-ECC group were higher than in the caries-free group. Prevalence of Bifidobacterium (p = 0.004) and S. wiggsiae (p < 0.001) in the S-ECC group was higher than in the caries-free group. The numbers of total bacteria (p = 0.003), Bifidobacterium (p < 0.001), and proportion of Bifidobacterium to total bacteria (p < 0.001) were higher in the S-ECC group. Detections of both bacteria, Bifidobacterium + S. wiggsiae (p < 0.001), were higher in the S-ECC group than in the caries-free group. In the S-ECC group, dmft scores (p < 0.001; p = 0.024) and the modified gingiva index (p = 0.004; p = 0.002) were higher in the presence of Bifidobacterium and S. wiggsiae, respectively. In the S-ECC group, the dmft scores (p = 0.005) and modified gingiva index (p = 0.004) were higher in the presence of both Bifidobacterium + S. wiggsiae. There were positive correlations between the Bifidobacterium level (p = 0.003), the proportion of Bifidobacterium to total bacteria (p = 0.017), and S-ECC. The level of Bifidobacterium (p < 0.001) and ratio of Bifidobacterium to total bacteria (p < 0.001) were correlated with the dmft score and modified gingival index in the S-ECC group. From the questionnaire, S-ECC were associated with major caregiver (p = 0.002), parent education levels (p = 0.02), prolonged bottle-feeding (>18 months) (p = 0.015), night-time feeding (p < 0.001), eating cariogenic snacks (p = 0.019), and frequency of dental visits (p = 0.003). Conclusions Levels of total bacteria, Bifidobacterium, S. wiggsiae and plaque, and the modified gingival indices were higher in the S-ECC group. Factors associated with S-ECC included the major caregiver, parent education levels, feeding patterns, cariogenic snacks consumption, and frequency of dental visits.

Dielectrophoresis: Measurement technologies and auxiliary sensing applications.

Dielectrophoresis (DEP), which arises from the interaction between dielectric particles and an aqueous solution in a nonuniform electric field, contributes to the manipulation of nano and microparticles in many fields, including colloid physics, analytical chemistry, molecular biology, clinical medicine, and pharmaceutics. The measurement of the DEP force could provide a more complete solution for verifying current classical DEP theories. This review reports various imaging, fluidic, optical, and mechanical approaches for measuring the DEP forces at different amplitudes and frequencies. The integration of DEP technology into sensors enables fast response, high sensitivity, precise discrimination, and label-free detection of proteins, bacteria, colloidal particles, and cells. Therefore, this review provides an in-depth overview of DEP-based fabrication and measurements. Depending on the measurement requirements, DEP manipulation can be classified into assistance and integration approaches to improve sensor performance. To this end, an overview is dedicated to developing the concept of trapping-on-sensing, improving its structure and performance, and realizing fully DEP-assisted lab-on-a-chip systems.

Research progress on the detection of foodborne pathogens based on aptamer recognition.

Foodborne diseases caused by bacterial contamination are a serious threat to food safety and human health. The classical plate culture method has the problems of long detection cycle, low sensitivity and specificity, and complicated operation, which cannot meet the growing demand for rapid quantitative detection of pathogenic bacteria. The frequent outbreak of foodborne diseases has put forward higher requirements for rapid and simple detection technology of foodborne pathogens. Aptamer is a kind of oligonucleotide fragment that can recognize targets with the advantages of high affinity and good specificity. The target can be range from proteins, small molecules, cells bacteria, and even viruses. Herein, the latest advances in sensitive and rapid detection of foodborne pathogens based on aptamer recognition was reviewed. Special attention has been paid to the obtained sequences of aptamers to various foodborne pathogens, the optimization of sequences, and the mechanism of aptamer recognition. Then, the research progress of biosensors for the detection of pathogenic bacteria based on aptamer recognition were summarized. Some challenges and prospects for the detection of foodborne pathogens based on aptamer recognition were prospected. In summary, with the further deepening of aptamer research and improvement of detection technology, aptamer-based recognition can meet the needs of rapid, sensitive, and accurate detection in practical applications.

Ultrasensitive and Highly Selective Detection of Staphylococcus aureus at the Single-Cell Level Using Bacteria-Imprinted Polymer and Vancomycin-Conjugated MnO2 Nanozyme.

Pathogenic bacterial infections, even at extremely low concentrations, pose significant threats to human health. However, the challenge persists in achieving high-sensitivity bacterial detection, particularly in complex samples. Herein, we present a novel sandwich-type electrochemical sensor utilizing bacteria-imprinted polymer (BIP) coupled with vancomycin-conjugated MnO2 nanozyme (Van@BSA-MnO2) for the ultrasensitive detection of pathogenic bacteria, exemplified by Staphylococcus aureus (S. aureus). The BIP, in situ prepared on the electrode surface, acts as a highly specific capture probe by replicating the surface features of S. aureus. Vancomycin (Van), known for its affinity to bacterial cell walls, is conjugated with a Bovine serum albumin (BSA)-templated MnO2 nanozyme through EDC/NHS chemistry. The resulting Van@BSA-MnO2 complex, serving as a detection probe, provides an efficient catalytic platform for signal amplification. Upon binding with the captured S. aureus, the Van@BSA-MnO2 complex catalyzes a substrate reaction, generating a current signal proportional to the target bacterial concentration. The sensor displays remarkable sensitivity, capable of detecting a single bacterial cell in a phosphate buffer solution. Even in complex milk matrices, it maintains outstanding performance, identifying S. aureus at concentrations as low as 10 CFU mL-1 without requiring intricate sample pretreatment. Moreover, the sensor demonstrates excellent selectivity, particularly in distinguishing target S. aureus from interfering bacteria of the same genus at concentrations 100-fold higher. This innovative method, employing entirely synthetic materials, provides a versatile and low-cost detection platform for Gram-positive bacteria. In comparison to existing nanozyme-based bacterial sensors with biological recognition materials, our assay offers distinct advantages, including enhanced sensitivity, ease of preparation, and cost-effectiveness, thereby holding significant promise for applications in food safety and environmental monitoring.

Detection of multidrug-resistant bacteria in the nasal cavities and evaluation of sinus disorders in patients undergoing Le Fort I osteotomy

IntroductionOrthognathic surgery can lead to sinus alterations, including sinusitis, attributed to the exposure of maxillary sinuses during Le Fort I osteotomy. Furthermore, being a hospital-based procedure, there is potential risk of complications arising from bacteria prevalent in such environments. This study evaluated maxillary sinusitis occurrence and the presence of multidrug-resistant bacteria in the nasal cavity before and after orthognathic surgery.MethodsTen patients with dentofacial deformities underwent Le Fort I osteotomy. Clinical evaluations using SNOT-22 questionnaire were performed, and nasal cavity samples were collected pre-surgery and 3–6 months post-surgery to quantify total mesophilic bacteria and detect Staphylococcus aureus, Acinetobacter baumannii, and Klebsiella pneumoniae. Cone Beam Computed Tomography (CBCT) was performed pre- and post-operatively, and the results were evaluated using the Lund-Mackay system. This study was registered and approved by the Research Ethics Committee of PUCRS (No. 4.683.066).ResultsThe evaluation of SNOT-22 revealed that five patients showed an improvement in symptoms, while two remained in the same range of interpretation. One patient developed post-operative maxillary sinusitis, which was not detected at the time of evaluation by SNOT-22 or CBCT. CBCT showed a worsening sinus condition in three patients, two of whom had a significant increase in total bacteria count in their nasal cavities. The Brodsky scale was used to assess hypertrophy in palatine tonsils, where 60% of the subjects had grade 1 tonsils, 20% had grade 2 and 20% had grade 3. None of the patients had grade 4 tonsils, which would indicate more than 75% obstruction. Two patients harboured S. aureus and K. pneumoniae in their nasal cavities. Notably, K. pneumoniae, which was multidrug-resistant, was present in the nasal cavity of patients even before surgery, but this did not result in maxillary sinusitis, likely due to the patients’ young and healthy condition.ConclusionThere was an improvement in signs and symptoms of maxillary sinusitis and quality of life in most patients after orthognathic surgery. However, some patients may still harbour multidrug-resistant bacteria, even if they are asymptomatic. Therefore, a thorough pre-operative assessment is essential to avoid difficult-to-treat post-operative complications.

Oral bacteria relative abundance in faeces increases due to gut microbiota depletion and is linked with patient outcomes.

The detection of oral bacteria in faecal samples has been associated with inflammation and intestinal diseases. The increased relative abundance of oral bacteria in faeces has two competing explanations: either oral bacteria invade the gut ecosystem and expand (the 'expansion' hypothesis), or oral bacteria transit through the gut and their relative increase marks the depletion of other gut bacteria (the 'marker' hypothesis). Here we collected oral and faecal samples from mouse models of gut dysbiosis (antibiotic treatment and DSS-induced colitis) and used 16S ribosomal RNA sequencing to determine the abundance dynamics of oral bacteria. We found that the relative, but not absolute, abundance of oral bacteria increases, reflecting the 'marker' hypothesis. Faecal microbiome datasets from diverse patient cohorts, including healthy individuals and patients with allogeneic haematopoietic cell transplantation or inflammatory bowel disease, consistently support the 'marker' hypothesis and explain associations between oral bacterial abundance and patient outcomes consistent with depleted gut microbiota. By distinguishing between the two hypotheses, our study guides the interpretation of microbiome compositional data and could potentially identify cases where therapies are needed to rebuild the resident microbiome rather than protect against invading oral bacteria.

Application of a clamshell isothermal nucleic acid amplification analyzer in the detection of lower respiratory tract bacteria

ObjectivesThe clamshell isothermal nucleic acid amplification analyzer RTisochip-S, a next-generation instrument featuring improved structural design, enhanced functional integration, reduced cost, and increased portability, was assessed for its suitability in clinical respiratory pathogens detection. MethodsThe certificated detection kit for lower respiratory tract bacteria (LRTB-kit) was applied to evaluate the performance of RTisochip-S via sensitivity, specificity, and repeatability analysis. The clinical specimens, including 51 sputum specimens and 10 bronchoalveolar lavage fluid specimens, were simultaneously detected on both RTisochip-S and a certificated reference instrument (RTisochip-A) to assess the consistency. ResultsThe results indicated that RTisochip-S fulfills the sensitivity, specificity, and repeatability requirements of the LRTB-Kit, and the results of clinical specimens on the two instruments were consistent. ConclusionsRTisochip-S is satisfying the clinical detection of respiratory pathogens while enhancing portability and compactness, making it more well-suited for point-of-care testing (POCT) applications.

Development and validation of a multi-target TaqMan qPCR method for detection of Borrelia burgdorferi sensu lato

Reliable detection of bacteria belonging to the Borrelia burgdorferi sensu lato species complex in vertebrate reservoirs, tick vectors, and patients is key to answer questions regarding Lyme borreliosis epidemiology. Nevertheless, the description of characteristics of qPCRs for the detection of B. burgdorferi s. l. are often limited. This study covers the development and validation of two duplex taqman qPCR assays used to target four markers on the chromosome of genospecies of B. burgdorferi s. l.Analytical specificity was determined with a panel of spirochete strains. qPCR characteristics were specified using water or tick DNA spiked with controlled quantities of the targeted DNA sequences of B. afzelii, B. burgdorferi sensu stricto or B. bavariensis. The effectiveness of detection results was finally evaluated using DNA extracted from ticks and biopsies from mammals whose infectious status had been determined by other detection assays.The developed qPCR assays allow exclusive detection of B. burgdorferi s. l. with the exception of the M16 marker which also detect relapsing fever Borreliae. The limit of detection is between 10 and 40 copies per qPCR reaction depending on the sample type, the B. burgdorferi genospecies and the targeted marker. Detection tests performed on various kind of samples illustrated the accuracy and robustness of our qPCR assays.Within the defined limits, this multi-target qPCR method allows a versatile detection of B. burgdorferi s. l., regardless of the genospecies and the sample material analyzed, with a sensitivity that would be compatible with most applications and a reproducibility of 100% under measurement conditions of limits of detection, thereby limiting result ambiguities.

A fluorescent sensor array based on antibiotic-stabilized metal nanoclusters for the multiplex detection of bacteria.

To address the need for facile, rapid detection of pathogens in water supplies, a fluorescent sensing array platform based on antibiotic-stabilized metal nanoclusters was developed for the multiplex detection of pathogens. Using five common antibiotics, eight different nanoclusters (NCs) were synthesized including ampicillin stabilized copper NCs, cefepime stabilized gold and copper NCs, kanamycin stabilized gold and copper NCs, lysozyme stabilized gold NCs, and vancomycin stabilized gold/silver and copper NCs. Based on the different interaction of each NC with the bacteria strains, unique patterns were generated. Various machine learning algorithms were employed for pattern discernment, among which the artificial neural networks proved to have the highest performance, with an accuracy of 100%. The developed prediction model performed well on an independent test dataset and on real samples gathered from drinking water, tap water and the Anzali Lagoon water, with prediction accuracy of 96.88% and 95.14%, respectively. This work demonstrates how generic antibiotics can be implemented for NC synthesis and used as recognition elements for pathogen detection. Furthermore, it displays how merging machine learning techniques can elevate sensitivity of analytical devices.

Evaluation of biofire filmarray meningitis/encephalitis assay for detection of bacteria, viruses, and yeast in cerebrospinal fluid specimens in the setting of a tertiary care hospital

Evaluation of biofire filmarray meningitis/encephalitis assay for detection of bacteria, viruses, and yeast in cerebrospinal fluid specimens in the setting of a tertiary care hospital

Functionalized carbon quantum dots fluorescent sensor array assisted by a machine learning algorithm for rapid foodborne pathogens identification

Food safety is a global concern, and conventional methods for detecting foodborne bacteria, such as polymerase chain reaction and enzyme-linked immunosorbent assay, often involve time-consuming processes, specialized equipment, or specific recognition of particular bacterial strains. There is an urgent need for more efficient and convenient detection methods for foodborne pathogens. This study addresses this need by introducing an easily constructed fluorescent sensor array for the identification of various foodborne bacteria. The sensor array comprises carbon quantum dots (CQDs) functionalized with ampicillin, polymyxin, and gentamicin, each exhibiting different affinities for binding with specific bacteria. Leveraging machine learning algorithms, the proposed sensor array enables rapid, accurate, and highly sensitive identification of foodborne pathogens. This approach offers a convenient solution for the development of rapid, accurate, and hypersensitive detection methods for multiple bioactive samples. In summary, the fluorescent sensor array in this study holds promise for advancing the field of foodborne bacteria detection.

Electrochemical platform for detecting Escherichia coli bacteria using machine learning methods

We present an electrochemical platform designed to reduce time of Escherichia coli bacteria detection from 24-48-hours to 30 minutes. The presented approach is based on a system which includes gallium-indium (eGaIn) alloy to provide conductivity and a hydrogel system to preserve bacteria and their metabolic species during the analysis. The work is dedicated to accurate and fast detection of Escherichia coli bacteria in different environments with the supply of machine learning methods. Electrochemical data obtained during the analysis is processed via multilayer perceptron model to identify i.e. predict bacterial concentration in the samples. The performed approach provides the effectiveness of bacteria identification in the range of 102 to 109 colony forming units per ml with the average accuracy of 97%. The proposed bioelectrochemical system combined with machine learning model is prospective for food analysis, agriculture, biomedicine.