Methods For Detection Of Pathogens Research Articles

Novel Efficient Selenium-Based D-π-A NIR Polymer Dots Anodic Electrochemiluminescence Emitter and Its Application in Simultaneous Detection of Two Pneumonia Pathogens with CdS Quantum Dots.

Community-acquired pneumonia (CAP) is a major cause of death in children under 5 years old globally. With Streptococcus pneumoniae (S. pneumoniae) and Mycoplasma pneumoniae (M. pneumoniae) being the main pathogens linked to CAP that requires hospitalization, there is an urgent need for a straightforward, cost-efficient, and highly accurate diagnostic method for immediate and early detection of CAP. In this work, benzo[1,2-c;4,5-c']bis([1,2,5]thiadiazole) (BBT) as π-bridge spacer with the donor unit of poly(9,9-dioctylfluorene) (PF) and the acceptor unit of dithienylbenzoselenadiazole (DBS) has been successfully copolymerized to unprecedentedly prepare novel D-π-A selenium-based polymer dots with efficient NIR electrochemiluminescence (named as Se-Pdots in this work). Se-Pdots exclusively generated excellent anodic ECL in the two-component coreaction system comprising TPrA and K2S2O8. Moreover, a potential-resolved ECL biosensor to simultaneously detect S. pneumoniae and M. pneumoniae has also been successfully constructed based on this novel Se-based NIR Pdots as an anodic emitter with CdS QDs as a cathodic emitter. Under optimal conditions, the biosensor has a wide linear range for S. pneumoniae (10-15 to 10-9 M) and M. pneumoniae (10-15 to 10-9 M), with low detection limits for S. pneumoniae (0.56 fM) and M. pneumoniae (0.96 fM). The proposed ECL biosensor provides a simple, sensitive, and reliable method for the simultaneous detection of CAP pathogens in clinical applications.

A one-pot loop-mediated isothermal amplification platform using fluorescent gold nanoclusters for rapid and naked-eye pathogen detection

Loop-mediated isothermal amplification (LAMP) is a rapid and sensitive nucleic acid testing method for pathogen detection, yet the absence of a straightforward readout strategy remains challenging. We've successfully designed polyethyleneimine-stabilized gold nanoclusters (PEI-AuNCs) as a cationic AuNCs indicator tailored for distinguishing LAMP results, enabling direct visual inspection under UV light. Positive LAMP reactions with PEI-AuNCs, in combination with magnesium pyrophosphate crystals, yield red-fluorescent bulk precipitates visible to the naked eye. To address contamination concerns, we introduced a one-pot reaction by incorporating AuNCs into the lid recess. This one-pot LAMP assay demonstrates exceptional detection capability, identifying Salmonella enterica at concentrations as low as 101 CFU/mL within approximately 50 min, excluding nucleic acid extraction. The platform's versatility, achieved through customizable primers, positions it as a promising molecular diagnostic tool for rapid and visual pathogen detection across scientific disciplines.

A novel high-throughput qPCR chip for solving co-infections in RAS farmed rainbow trout

Recirculating aquaculture systems (RAS) have become more attractive due to reduced water consumption and effluent discharge. However, intensification of production increases the risk of introducing pathogens at farming sites. The emergence of uncultivable pathogens and RAS pathobiome diversity shifts the traditional disease paradigm from “one pathogen, one disease” to complex multiple-pathogen disease cases. Piscine orthoreovirus genotype 3 (PRV-3) is an excellent example, as it is capable of inducing anemia and heart pathology resembling heart and skeletal muscle inflammation under experimental conditions, and is associated with increased mortality in association with other pathogens in the field. The aim of this study was to develop a method for detection of multiple pathogens and putative pathogens, as co-infections are common in aquaculture. To do this, in the pilot study, we mapped the pathobiome of RAS-farmed rainbow trout (Oncorhynchus mykiss) (commercial RAS, farm A) using both standard diagnostic methods and metabarcording (16S rRNA) to investigate the gill microbiome. During this study, we observed infections with multiple pathogens, and detected two putative gill pathogens Candidatus Branchiomonas cysticola and Candidatus Piscichlamydia salmonis, both of which have been linked with complex gill disease in Atlantic salmon (Salmo salar). Based on the pilot study, we developed and tested a high throughput qPCR (HT-qPCR) chip targeting 22 viral and bacterial pathogens and putative pathogens, followed by a surveillance of a fish cohort in a commercial RAS farm during production (farm B). Co-infection with PRV-3 and Ca. B. cysticola combined with stress inducing management practices may explain the severe disease outbreak observed (37% mortality). The time course study sets the base for a future screening scheme for disease prediction and addresses limitations of the method when testing environmental DNA/RNA.

Advancing Microfluidic Immunity Testing Systems: New Trends for Microbial Pathogen Detection.

Pathogenic microorganisms play a crucial role in the global disease burden due to their ability to cause various diseases and spread through multiple transmission routes. Immunity tests identify antigens related to these pathogens, thereby confirming past infections and monitoring the host's immune response. Traditional pathogen detection methods, including enzyme-linked immunosorbent assays (ELISAs) and chemiluminescent immunoassays (CLIAs), are often labor-intensive, slow, and reliant on sophisticated equipment and skilled personnel, which can be limiting in resource-poor settings. In contrast, the development of microfluidic technologies presents a promising alternative, offering automation, miniaturization, and cost efficiency. These advanced methods are poised to replace traditional assays by streamlining processes and enabling rapid, high-throughput immunity testing for pathogens. This review highlights the latest advancements in microfluidic systems designed for rapid and high-throughput immunity testing, incorporating immunosensors, single molecule arrays (Simoas), a lateral flow assay (LFA), and smartphone integration. It focuses on key pathogenic microorganisms such as SARS-CoV-2, influenza, and the ZIKA virus (ZIKV). Additionally, the review discusses the challenges, commercialization prospects, and future directions to advance microfluidic systems for infectious disease detection.

Update on tick-borne pathogens detection methods within ticks

Ticks are known vectors of various pathogens, including bacteria, parasites and viruses, that impact both animal and human health. Improving knowledge of the distribution of tick-borne pathogens, combined with their early detection in ticks, are essential steps to fight against tick-borne diseases and mitigate their impacts. Here we give an overview of what are the common methods of pathogen detection in tick samples, including recent developments concerning how to handle tick samples, get access to tick-borne pathogens by chemical or physical disruption of the ticks, and methods used for the RNA/DNA extraction steps. Furthermore, we discuss promising tools that are developed for other sample types such as serum or blood to detect tick-borne pathogens, and those that could be used in the future for tick samples.

3D printed microfluidic chip integrated with nanointerferometer for multiplex detection of foodborne pathogens

The current foodborne pathogen detection methods, such as culture-based methods, polymerase chain reaction, and optical and electrochemical biosensors with nucleic acid, have high sensitivity and selectivity. However, they are slow, expensive, and require well-trained operators. In this study, we utilized a 3D printer to develop a novel chip with an aptamer-based nanointerferometer capable of identifying four distinct foodborne pathogens: Listeria monocytogenes, Escherichia coli, Salmonella typhimurium, and Staphylococcus aureus. The aptamer sensor on the chip achieved a limit-of-detection of 10 colony forming unit (CFU)/ml. With its high sensitivity and specificity, this chip offers a cost-effective platform for distinguishing and screening different foodborne pathogens.

Sensitive and rapid identification of pathogens by droplet digital PCR in a cohort of septic patients: a prospective diagnostic study

Background There is a critical need for a rapid and sensitive pathogen detection method for septic patients. This study aimed to investigate the diagnostic efficacy of Digital droplet polymerase chain reaction (ddPCR) in identifying pathogens among suspected septic patients. Methods We conducted a prospective pilot diagnostic study to clinically validate the multiplex ddPCR panel in diagnosing suspected septic patients. A total of 100 sepsis episodes of 89 patients were included in the study. Results In comparison to blood culture, the ddPCR panel exhibited an overall sensitivity of 75.0% and a specificity of 69.7%, ddPCR yielded an additional detection rate of 17.0% for sepsis cases overall, with a turnaround time of 2.5 h. The sensitivity of ddPCR in the empirical antibiotic treatment and the non-empirical antibiotic treatment group were 78.6% versus 80.0% (p > 0.05). Antimicrobial resistance genes were identified in a total of 13 samples. Whenever ddPCR detected the genes beta-lactamase-Klebsiella pneumoniae carbapenemase (blaKPC) or beta-lactamase-New Delhi metallo (blaNDM), these findings corresponded to the cultivation of carbapenem-resistant gram-negative bacteria. Dynamic ddPCR monitoring revealed a consistent alignment between the quantitative ddPCR results and the trends observed in C-reactive protein and procalcitonin levels. Conclusions Compared to blood culture, ddPCR exhibited higher sensitivity for pathogen diagnosis in suspected septic patients, and it provided pathogen and drug resistance information in a shorter time. The quantitative results of ddPCR generally aligned with the trends seen in C-reactive protein and procalcitonin levels, indicating that ddPCR can serve as a dynamic monitoring tool for pathogen load in septic patients.

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.

Agreement of antimicrobial susceptibility testing of Pasteurella multocida and Mannheimia haemolytica found in pre-weaned dairy calves with bovine respiratory disease

Bovine respiratory disease (BRD) is one of the primary dis­eases affecting pre-weaned dairy calves and involves respi­ratory pathogens, such as Mannheimia haemolytica (Mh) and Pasteurella multocida (Pm). While agreement between methods for detection of bacterial pathogens in dairy calves with BRD is very good, there are limited data regarding how antimicro­bial susceptibility (AS) of isolates collected via these methods agree. The objective was to evaluate agreement among the AS profiles of Mh or Pm obtained by transtracheal wash (TTW), nasal swab (NS), nasopharyngeal swab (DNP), and bronchoal­veolar lavage (BAL) in pre-weaned dairy calves with BRD that were positive in all 4 samples.

Enhancing pathogen detection and characterization of respiratory microbiome signatures of infection through next-generation sequencing

Next-generation sequencing-based (NGS) methods for pathogen detection, which can capture the entire microbial composition in a clinical sample, are used strategically in parallel to culture-based methods. While NGS-based methods cannot confirm organism viability, culture-based methods can but are limited by the number of culture conditions routinely utilized in clinical microbiology laboratories. The relatively wide scope provided by sequencing compensates for the limited scope of culture-based methods but creates obstacles in distinguishing pathogens from an expected body-site-specific microbiome or benign transient colonizers. This study compares NGS-based methods for pathogen detection in respiratory samples to current diagnostics at Texas Children's Hospital in Houston, Texas. Current diagnostics include various culture-based assays, targeted PCR assays, and reference laboratory-generated sequencing. We hypothesize that employing sample metadata (source, type, etc.) and patient data (clinical history, chronic conditions, etc.) during data analysis will help distinguish pathogens from expected flora in respiratory samples. To develop these methods, 27 respiratory samples with suffcient volume for both routine diagnostic testing and this study were collected. Nucleic acid was extracted using the Qiagen DNeasy PowerSoil Pro Kit after collection, and targeted short-read sequencing (16S, 18S/ITS) was performed. These data were then analyzed using a custom bioinformatic pipeline built around Qiime2-2022. In brief, sequences are denoised and quality filtered using DADA2, an algorithm that uses a statistical model for correcting sequencing errors, after which similar amplicon sequence variants (ASVs) are clustered. Next, a feature table of ASVs that are 100% identical is generated, and taxonomy assigned using a naive Bayes taxonomy classifier against the Silva 13.2 database. Finally, unassigned and low abundance ASVs are removed. When species-level identification couldn't be determined through targeted short-read sequencing, untargeted long-read sequencing was used. In one case, we found that a bronchoalveolar lavage sample from the lung of a patient with a history of recurrent pneumonia contained a singular pathogenic bacterium, H. influenzae. This finding agreed with results obtained through reference laboratory-generated sequencing. In another case, we identified >14 unique bacteria at varying concentrations in a wash sample collected from the lung of an asymptomatic patient during a routine bronchoscopy. These findings, however, were determined to be expected respiratory flora. Our NGS-based methods’ enhanced pathogen detection compared to current diagnostics and discriminates between respiratory flora and active infections. Setting thresholds for pathogen detection, evaluating clinical relevance in the context of body site and presentation, and deploying additional molecular techniques when necessary are crucial steps to increase the accuracy of pathogen detection in the clinic. This study was supported by the Texas Children's Hospital Department of Pathology. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Clinical application of metagenomic next-generation sequencing for the diagnosis of suspected infection in adults: A cross-sectional study.

Metagenomic next-generation sequencing (mNGS) has become an available method for pathogen detection. The clinical application of mNGS requires further evaluation. We conducted a cross-sectional study of 104 patients with suspected infection between May 2019 and May 2021. The risk factors associated with infection were analyzed using univariate logistic analysis. The diagnostic performance of pathogens was compared between mNGS and conventional microbiological tests. About 104 patients were assigned into 3 groups: infected group (n = 69), noninfected group (n = 20), and unknown group (n = 15). With the composite reference standard (combined results of all microbiological tests, radiological testing results, and a summary of the hospital stay of the patient) as the gold standard, the sensitivity, specificity, positive predictive value, negative predictive value of mNGS was 84.9%, 50.0%, 88.6%, and 42.1%, respectively. Compared with conventional microbiological tests, mNGS could detect more pathogens and had obvious advantages in Mycobacterium tuberculosis, Aspergillus, and virus detection. Moreover, mNGS had distinct benefits in detecting mixed infections. Bacteria-fungi-virus mixed infections were the most common in patients with severe pneumonia. mNGS had a higher sensitivity than conventional microbiological tests, especially for M. tuberculosis, Aspergillus, viruses, and mixed infections. We suggest that mNGS should be used more frequently in the early diagnosis of pathogens in critically ill patients in the future.

Cascaded signal amplification strategy for ultra-specific, ultra-sensitive, and visual detection of Shigella flexneri.

Pathogen infections including Shigella flexneri have posed a significant threat to human health for numerous years. Although culturing and qPCR were the gold standards for pathogen detection, time-consuming and instrument-dependent restrict their application in rapid diagnosis and economically less-developed regions. Thus, it is urgently needed to develop rapid, simple, sensitive, accurate, and low-cost detection methods for pathogen detection. In this study, an immunomagnetic beads-recombinase polymerase amplification-CRISPR/Cas12a (IMB-RPA-CRISPR/Cas12a) method was built based on a cascaded signal amplification strategy for ultra-specific, ultra-sensitive, and visual detection of S. flexneri in the laboratory. Firstly, S. flexneri was specifically captured and enriched by IMB (Shigella antibody-coated magnetic beads), and the genomic DNA was released and used as the template in the RPA reaction. Then, the RPA products were mixed with the pre-loaded CRISPR/Cas12a for fluorescence visualization. The results were observed by naked eyes under LED blue light, with a sensitivity of 5CFU/mL in a time of 70min. With no specialized equipment or complicated technical requirements, the IMB-RPA-CRISPR/Cas12a diagnostic method can be used for visual, rapid, and simple detection of S. flexneri and can be easily adapted to monitoring other pathogens.

Establishment and application of a quadruplex real-time RT-qPCR assay for differentiation of TGEV, PEDV, PDCoV, and PoRVA

Porcine viral diarrhea is a common ailment in clinical settings, causing significant economic losses to the swine industry. Notable culprits behind porcine viral diarrhea encompass transmissible gastroenteritis virus (TGEV), porcine epidemic diarrhea virus (PEDV), porcine deltacoronavirus (PDCoV), and porcine rotavirus-A (PoRVA). Co-infections involving the viruses are a common occurrence in clinical settings, thereby amplifying the complexities associated with differential diagnosis. As a consequence, it is therefore necessary to develop a method that can detect and differentiate all four porcine diarrhea viruses (TGEV, PEDV, PDCoV, and PoRVA) with a high sensitivity and specificity. Presently, polymerase chain reaction (PCR) is the go-to method for pathogen detection. In comparison to conventional PCR, TaqMan real-time PCR offers heightened sensitivity, superior specificity, and enhanced accuracy. This study aimed to develop a quadruplex real-time RT-qPCR assay, utilizing TaqMan probes, for the distinctive detection of TGEV, PEDV, PDCoV, and PoRVA. The quadruplex real-time RT-qPCR assay, as devised in this study, exhibited the capacity to avoid the detection of unrelated pathogens and demonstrated commendable specificity, sensitivity, repeatability, and reproducibility, boasting a limit of detection (LOD) of 27 copies/μL. In a comparative analysis involving 5483 clinical samples, the results from the commercial RT-qPCR kit and the quadruplex RT-qPCR for TGEV, PEDV, PDCoV, and PoRVA detection were entirely consistent. Following sample collection from October to March in Guangxi Zhuang Autonomous Region, we assessed the prevalence of TGEV, PEDV, PDCoV, and PoRVA in piglet diarrhea samples, revealing positive detection rates of 0.2 % (11/5483), 8.82 % (485/5483), 1.22 % (67/5483), and 4.94 % (271/5483), respectively. The co-infection rates of PEDV/PoRVA, PEDV/PDCoV, TGEV/PED/PoRVA, and PDCoV/PoRVA were 0.39 %, 0.11 %, 0.01 %, and 0.03 %, respectively, with no detection of other co-infections, as determined by the quadruplex real-time RT-qPCR. This research not only established a valuable tool for the simultaneous differentiation of TGEV, PEDV, PDCoV, and PoRVA in practical applications but also provided crucial insights into the prevalence of these viral pathogens causing diarrhea in Guangxi.

LAMP assay to detect Elsinoë necatrix; an important Eucalyptus shoot and leaf pathogen.

Eucalyptus scab and shoot malformation caused by Elsinoë necatrix is an emerging disease and a serious threat to the global commercial forestry industry. The disease was first discovered in North Sumatra, Indonesia and now requires a simple and effective method for early pathogen detection. In this study, a rapid and sensitive Loop-mediated isothermal amplification (LAMP) assay was developed for E. necatrix. A unique region in a secondary metabolite gene cluster was used as target for the assay. To test robustness of the assay, LAMP amplification was verified in 15 strains of E. necatrix. A specificity test against 23 closely related Elsinoë species and three fungal species commonly isolated on Eucalyptus showed that the LAMP assay exclusively identified E. necatrix isolates. The assay had a high level of sensitivity, able to detect 0.01 ng (approximately 400 target copies) of pure E. necatrix DNA. Furthermore, using a simple DNA extraction method, it was possible to use this assay to detect E. necatrix in infected Eucalyptus leaves.

One-pot dual-CRISPR/Cas12b-mediated dUTP-LAMP for rapid and sensitive detection of foodborne pathogens without carryover contamination

Rapid and accurate detection of foodborne pathogens is of great significance for ensuring food safety. Currently, the CRISPR-Dx based on Cas12b, a new and better performing Cas enzyme, is very rare, and the vast majority require a two-step method, facing aerosol contamination. In this work, we reported a one-pot dual-CRISPR/Cas12b mediated dUTP-LAMP method for rapid and sensitive detection of foodborne pathogens without nucleic acid extraction and contamination-free. The design mechanism of sgRNAs in the one-pot CRISPR/Cas12b-mediated LAMP method was investigated in detail for the first time. Moreover, a novel PAM sequence UUN of AapCas12b was discovered, and combined with dUTP-LAMP system for one-pot dual-sgRNA detection without carryover contamination. Our developed method can achieve high specificity, nucleic acid extraction-free detection of 2.33 × 104 CFU/mL Salmonella within 1 h. Furthermore, accurate detection of Salmonella was successfully performed in real samples of milk, fruit and egg, demonstrating the practical significance of the developed method.

Recent advances in the biosensors application for reviving infectious disease management in silkworm model: a new way to combat microbial pathogens.

Silkworms are an essential economic insect but are susceptible to diseases during rearing, leading to yearly losses in cocoon production. While chemical control is currently the primary method to reduce disease incidences, its frequent use can result in loss of susceptibility to pathogens and, ultimately, antibiotic resistance. To effectively prevent or control disease, growers must accurately, sensitively, and quickly detect causal pathogens to determine the best management strategies. Accurate recognition of diseased silkworms can prevent pathogen transmission and reduce cocoon loss. Different pathogen detection methods have been developed to achieve this objective, but they need more precision, specificity, consistency, and promptness and are generally unsuitable for in-situ analysis. Therefore, detecting silkworm diseases under rearing conditions is still an unsolved problem. As a consequence of this, there is an enormous interest in the development of biosensing systems for the early and precise identification of pathogens. There is also significant room for improvement in translating novel biosensor techniques to identify silkworm pathogens. This study explores the types of silkworm diseases, their symptoms, and their causal microorganisms. Moreover, we compare the traditional approaches used in silkworm disease diagnostics along with the latest sensing technologies, with a precise emphasis on lateral flow assay-based biosensors that can detect and manage silkworm pathogens.

Comparison of metagenomic next-generation sequencing and conventional culture for the diagnostic performance in febrile patients with suspected infections

BackgroundTimely and accurate identification of pathogens is crucial for appropriate treatment and prognosis of infectious diseases. As an increasingly popular pathogen detection method, the performance of metagenomic next-generation sequencing (mNGS) in detecting pathogens in febrile patients with suspected infection requires further exploration.MethodsThis study included 368 febrile patients with suspected infections who were admitted to the Infectious Disease Department of Qilu Hospital, Shandong University between January 5, 2021 and April 14, 2023. Both mNGS testing and conventional culture were performed in all patients. Clinical data of enrolled patients were collected, and the diagnostic performances of mNGS and culture were compared.ResultsOf the 368 enrolled patients, 231 were finally diagnosed with infection and 137 were with diseases other than infection. The sensitivity (58.01% vs. 21.65%, p < 0.001) and negative predictive value (54.67% vs. 42.9%) of mNGS were superior to those of culture. In contrast, the culture exhibited higher specificity (99.27% vs. 85.40%, p < 0.001) and positive predictive value (98.84% vs. 87.01%) than mNGS. Among infected patients with positive mNGS results, 64 received adjusted antibiotic therapy including treatment transitions, antibiotic downgrading, and combination therapy. Among them, 9 had additional antifungal drugs and 21 patients had a treatment turning point based on the mNGS results and these patients recovered and discharged due to timely antibiotic adjustment. Both positive rates of puncture fluid mNGS and tissue mNGS were higher than those of culture in the patients who had prior antibiotic use, and this difference was statistically significant (p = 0.000).ConclusionmNGS is more sensitive and accurate than traditional culture, making it ideal for identifying pathogens and screening infectious diseases, especially for those with uncultivated or difficult-to-cultivate species. Early diagnosis allows for prompt treatment with targeted antibiotics, and mNGS is recommended when samples are limited.

Development of an Immunocapture-Based Polymeric Optical Fiber Sensor for Bacterial Detection in Water.

Conventional methods for pathogen detection in water rely on time-consuming enrichment steps followed by biochemical identification strategies, which require assay times ranging from 24 hours to a week. However, in recent years, significant efforts have been made to develop biosensing technologies enabling rapid and close-to-real-time detection of waterborne pathogens. In previous studies, we developed a plastic optical fiber (POF) immunosensor using an optoelectronic configuration consisting of a U-Shape probe connected to an LED and a photodetector. Bacterial detection was evaluated with the immunosensor immersed in a bacterial suspension in water with a known concentration. Here, we report on the sensitivity of a new optoelectronic configuration consisting of two POF U-shaped probes, one as the reference and the other as the immunosensor, for the detection of Escherichia coli. In addition, another methos of detection was tested where the sensors were calibrated in the air, before being immersed in a bacterial suspension and then read in the air. This modification improved sensor sensitivity and resulted in a faster detection time. After the immunocapture, the sensors were DAPI-stained and submitted to confocal microscopy. The histograms obtained confirmed that the responses of the immunosensors were due to the bacteria. This new sensor detected the presence of E. coli at 104 CFU/mL in less than 20 min. Currently, sub-20 min is faster than previous studies using fiber-optic based biosensors. We report on an inexpensive and faster detection technology when compared with conventional methods.

Development of a Bioaerosol Sampling Method for Airborne Pathogen Detection with Focus on SARS-CoV-2

As worldwide evidence shows that the predominant transmission route of SARS-CoV-2 and other respiratory pathogens is airborne, the need for suitable methods for the sampling of bioparticles directly from the air is more urgent than ever. The present paper describes the development of a method for the collection of biological aerosols, using a preexisting cyclonic impinger, the Coriolis μ, combined with a lysis buffer and subsequent qPCR analysis of the generated samples in lab. Four phases of method development are described: exploratory, validation, blank tests, and application. The application phase consisted of a field experiment in which the method was simultaneously applied at two daycare facilities. The method achieved a good level of accuracy and reliability in detecting different types of infectious agents in the air, with a global uncertainty of 19.6%. Furthermore, our method allows the simultaneous detection of 26 different respiratory pathogens in air samples, it is relatively simple, and the equipment is easy to use. Additionally, the time to collect a representative sample is short compared to other methods. The method does not cause significant disturbance to those present in the sampled rooms, and it is safe for operators and flexible, meaning it can be used in virtually any environment regardless of use, size, or occupancy. Further research is being developed to allow quantitative analysis of the collected samples and to test the methods’ ability to assess the viability of the microorganisms collected in the sample.

Development of a 3D Microfluidic Analytical Device for the Detection of Pathogenic Bacteria in Commercial Food Samples with Loop-Mediated Isothermal Amplification

Traditional methods of detecting foodborne pathogens take several days to produce the required results. Furthermore, various molecular techniques (e.g., PCR) that also produce reliable results in the detection of pathogenic bacteria have been introduced, but the cost–time ratio required does not allow them to be considered a substantial solution to this specific problem. Three-dimensional (3D) printing technology provides the ability to design and manufacture microfluidic analytical devices using conventional 3D printers, which, in combination with colorimetric loop-mediated isothermal amplification (LAMP), may further simplify the process. The overall reduction in time and cost may provide the opportunity to upscale this diagnostic modality. Moreover, unlike most microfluidic analytical devices, this technique is simpler and more user-friendly, as it does not require any expertise or additional equipment apart from a conventional oven. A 3D-printed microfluidic analytical device in combination with LAMP was developed and tested for the simultaneous detection of foodborne pathogens in food samples. A total of 150 commercial food specimens (50 milk, 50 chicken, 50 lettuce samples) were analyzed for possible contamination with Salmonella typhimurium, Listeria monocytogenes and Escherichia coli. The 3D-printed microfluidic device was 100% precise for both negative (80 samples) and positive samples (7 samples were positive for S. typhimurium, 28 for L. monocytogenes, and 35 for E. coli) for all pathogens. Overall, the amount of data analyzed led to a high level of confidence in the precision of this device. As such, this new 3D device in combination with LAMP provides a precise detection method for food pathogens with a low detection limit.