Detection Of Respiratory Pathogens Research Articles

Laboratory validation of a clinical metagenomic next-generation sequencing assay for respiratory virus detection and discovery.

Tools for rapid identification of novel and/or emerging viruses are urgently needed for clinical diagnosis of unexplained infections and pandemic preparedness. Here we developed and clinically validated a largely automated metagenomic next-generation sequencing (mNGS) assay for agnostic detection of respiratory viral pathogens from upper respiratory swab and bronchoalveolar lavage samples in <24 h. The mNGS assay achieved mean limits of detection of 543 copies/mL, viral load quantification with 100% linearity, and 93.6% sensitivity, 93.8% specificity, and 93.7% accuracy compared to gold-standard clinical multiplex RT-PCR testing. Performance increased to 97.9% overall predictive agreement after discrepancy testing and clinical adjudication, which was superior to that of RT-PCR (95.0% agreement). To enable discovery of novel, sequence-divergent human viruses with pandemic potential, de novo assembly and translated nucleotide algorithms were incorporated into the automated SURPI+ computational pipeline used by the mNGS assay for pathogen detection. Using in silico analysis, we showed that after removal of all human viral sequences from the reference database, 70 (100%) of 70 representative human viral pathogens could still be identified based on homology to related animal or plant viruses. Our assay, which was granted breakthrough device designation from the US Food and Drug Administration (FDA) in August of 2023, demonstrates the feasibility of routine mNGS testing in clinical and public health laboratories, thus facilitating a robust and rapid response to the next viral pandemic.

Transforming Bacterial Lower Respiratory Tract Infection Diagnosis: A Study on the Efficiency of the FilmArray Pneumonia Panel

Abstract Background: Lower respiratory tract infections (LRTIs) significantly contribute to global morbidity and mortality. Conventional bacterial LRTIs diagnosis relies on microbiological methods, which are time-consuming. The Biofire® FilmArray® Pneumonia Panel (FAPP) offers a faster and more accurate detection of respiratory pathogens but shows conflicting results with conventional cultures. Aim: We assessed the agreement between bacterial organisms and resistance genes identified using FAPP and standard culture techniques. Methods: This single-center retrospective study analyzed 400 patient samples, comparing the positive predictive value (PPV), negative predictive value (NPV), sensitivity, and specificity with conventional cultures. The prevalence of bacterial organisms and resistance markers in FAPP and cultures was estimated. Results: In 400 samples, 692 bacterial targets and 216 resistance markers were detected using FAPP. FAPP detection was 3.9 times higher than bacterial culture. The overall PPV, NPV, sensitivity, and specificity were 23.55%, 99.76%, 92.61%, and 90.92%, respectively. Multiple pathogens were found in 177 samples (46.3%) with FAPP. Conclusion: FAPP provides rapid and sensitive detection of respiratory bacterial infections. However, results should be interpreted with the clinical context. Further studies are needed to clarify its clinical impact and cost-effectiveness.

Early-life Upper Airway Microbiota are Associated with Decreased Lower Respiratory Tract Infections.

Microbial interactions mediating colonization resistance play key roles within the human microbiome, shaping susceptibility to infection from birth. To gain insight into microbiome-mediated defenses and respiratory pathogen colonization dynamics, we sequenced and analyzed nasal (n=229) and oral (n=210) microbiomes with associated health/environmental data from our Wisconsin Infant Study Cohort at age 24-months. Participants with early-life lower respiratory tract infection (LRTI) were more likely to be formula-fed, attend daycare, and experience wheezing. Shotgun metagenomic sequencing with detection of viral and bacterial respiratory pathogens revealed nasal microbiome composition to associate with prior LRTI - namely lower alpha diversity, depletion of Prevotella, and enrichment of Moraxella catarrhalis including drug-resistant strains. Prevotella originating from healthy microbiomes had higher biosynthetic gene cluster abundance and exhibited contact-independent inhibition of M. catarrhalis, suggesting interbacterial competition impacts nasal pathogen colonization. This work advances understanding of protective host-microbial interactions occurring in airway microbiomes that alter infection susceptibility in early-life.

Porcine Nose Atrophy Assessed by Automatic Imaging and Detection of Bordetella bronchiseptica and Other Respiratory Pathogens in Lung and Nose.

The nasal mucosa is a crucial filtering organ to prevent attachment and invasion of pathogens. To assess nasal health in relation to lung health, transverse cross sections of the nasal turbinates of 121 pigs suffering from respiratory disease and sent for diagnostic necropsy were scored visually and by an artificial intelligence (AI) medical diagnostic application (AI DIAGNOS), resulting in a high correlation of both scores (p < 0.001). Nasal samples of the diseased pigs were examined only for Bordetella (B.) bronchiseptica (PCR and bacteriological culture) and Pasteurella (P.) multocida (bacteriological culture). All pigs showed various degrees of inflammatory lung tissue alterations, and 35.5% of the pigs had atrophy of the nasal turbinates with no relation to detection rates of B. bronchiseptica (54.5%) and P. multocida (29.0%) in the nose. All P. multocida strains from nose samples were negative for the toxA gene so non-progressive atrophic rhinitis was diagnosed. Pigs positive for B. bronchiseptica in the nose were more often positive for B. bronchiseptica in the lung (p < 0.001) and for other bacterial species in the lower respiratory tract (p = 0.005). The new diagnostic application for scoring cross sections of nasal turbinates is a valuable tool for a fast and reproducible diagnostic.

A Multicenter, Longitudinal Maternal and Birth Cohort Study in Latin America to Assess Prevalent Respiratory Tract Infections in Children from 0 to 5 Years of Age. The MINERVAL Study

Abstract Background A maternal and birth cohort study can assess the etiology and clinical course of lower respiratory tract infections and offers the opportunity to evaluate the relationship between sociodemographic, clinical, host characteristics and disease severity. In Latin America, a consortium of clinical research centers in Colombia and Panama has demonstrated its ability to conduct long-term longitudinal studies involving active surveillance of thousands of children with consistent retention rates. The MINERVAL cohort study aims to estimate the incidence, etiology, severity, and burden of lower respiratory tract infections (LRTI) and to identify microbiome and transcriptome profiles to help predict risk and assess disease severity in children from birth to 5 years of age. Methods We are establishing a maternal/birth cohort study in four sites (Cali, Bogota, Barranquilla and Panama), and will be recruiting 542 participants per center. Enrolled pregnant women between 24 and 27 weeks of gestation, and newborns under 4 weeks of age, will be closely followed with active surveillance weekly during the first 2 years for early detection of LRTI. Monthly telephone follow-up calls will continue until five years of age to assess the development of long-term respiratory morbidity and complications, including recurrent wheezing episodes. Clinical samples (NP swabs -for respiratory pathogen detection and microbiome analysis-, and blood -for cytokine and transcriptome analysis-) will be obtained in pregnant women, and in infants in the first 4 weeks of life and every 6 months for two years. Women and children who develop LRTI during the longitudinal follow-up will be evaluated clinically and samples will be collected. Results This cohort will provide prospective data and biological samples at crucial stages of children’s development, to allow estimation of the incidence and burden of LRTI by age and etiology, and the identification of risk factors and possible targets for intervention. Furthermore, the use of transcriptional profiling will allow early identification of variables to predict and guide clinical management in children, the use of antivirals and monoclonal antibodies, and to prioritize the population to be vaccinated according to age and risk factors. Conclusion The establishment of observational maternal and birth cohorts in Latin America could provide information to guide the development of strategies to prevent and mitigate the impact of respiratory tract infections in young children. Collaboration among investigators in the region and partnerships with international investigators optimizes resources and allows standardization of good surveillance practices, data exchange and the generation of new knowledge for future studies.

Design and implementation of a metagenomic analytical pipeline for respiratory pathogen detection

ObjectiveWe developed an in-house bioinformatics pipeline to improve the detection of respiratory pathogens in metagenomic sequencing data. This pipeline addresses the need for short-time analysis, high accuracy, scalability, and reproducibility in a high-performance computing environment.ResultsWe evaluated our pipeline using ninety synthetic metagenomes designed to simulate nasopharyngeal swab samples. The pipeline successfully identified 177 out of 204 respiratory pathogens present in the compositions, with an average processing time of approximately 4 min per sample (processing 1 million paired-end reads of 150 base pairs). For the estimation of all the 470 taxa included in the compositions, the pipeline demonstrated high accuracy, identifying 420 and achieving a correlation of 0.9 between their actual and predicted relative abundances. Among the identified taxa, 27 were significantly underestimated or overestimated, including only three clinically relevant pathogens. We also validated the pipeline by applying it to a clinical dataset from a study on metagenomic pathogen characterization in patients with acute respiratory infections and successfully identified all pathogens responsible for the diagnosed infections. These findings underscore the pipeline’s effectiveness in pathogen detection and highlight its potential utility in respiratory pathogen surveillance.

A-276 Unraveling Pathogen Dynamics In Pediatric Meningitis Complications During The Omicron Variant Outbreak In Taiwan

Abstract Background Taiwan, once celebrated for its remarkable control over COVID-19, faced an unexpected surge in pediatric cases during the first wave of the omicron variant in April 2022. Alarming data revealed acute encephalitis emerging in half of the severe or fatal COVID-19 cases in children within the initial two months of the omicron epidemic. This study delves into the intricate microbiota patterns and viral pathogens contributing to encephalitis complications in affected children. Methods The study enrolled 36 pediatric patients, comprising 11 patients with severe encephalitis, 12 patients with mild encephalitis, and 13 normal controls. Nasal swabs were collected for pathogen detection. For respiratory microbiota analysis, 16S rRNA metagenomic sequencing was employed, while the Illumina Respiratory Pathogen ID/AMR Enrichment Panel was used for respiratory pathogen identification. Results Microbiota analysis of nasal swabs from COVID-19 pediatric patients with meningitis complications revealed prevalent Corynebacterium, Staphylococcus, Dolosigranulum, Acinetobacter, Moraxella, and Streptococcus. Conversely. No predominant bacterial species were detected in the normal control group. Nasal swab respiratory pathogen detection identified coinfections, particularly Herpesviridae viruses such as human herpesvirus 6, Epstein-Barr virus, and Cytomegalovirus in pediatric patients with meningitis complications. Notably, two severe encephalitis cases exhibited coinfections involving rhinovirus, SARS-CoV-2, and Herpesviridae viruses (HHV-6, EBV). In one fatal case, distribution of Streptococcus genes among total geneomes reaches 40.69%, 7 drug resistant genes were detected. Conclusions This study suggests a potential link between latent Herpesviridae virus coinfections (HHV-6, CMV, EBV) and meningitis complications in pediatric patients. Furthermore, the presence of a secondary respiratory virus (rhinovirus) coinfection appears to be associated with severe complications. These findings shed light on the complex pathogen dynamics contributing to the emergence of encephalitis in pediatric COVID-19 cases during the omicron variant outbreak in Taiwan.

Low-cost high-throughput targeted sequencing for the accurate detection of respiratory tract pathogens.

The current gold standard for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) diagnosis by real-time reverse transcriptase polymerase chain reaction (RT-PCR) is limited by the number of genes that can be detected. In this study, we developed a low-cost and high-throughput next-generation sequencing technology that can overcome the limitations of real time RT-PCR. A targeted sequencing panel (TSP) consisting of approximately 500 amplicons was designed. This panel could simultaneously detect a broad range of gene loci of SARS-CoV-2, and genes for the most common infectious viruses that affect the respiratory tract, in a single run and could include up to 96 samples. Four hundred and forty-eight samples and 31 control samples were analyzed independently with both TSP and RT-PCR, and the results were compared for accuracy and other indicators. TSP identified 50 SARS-CoV-2 positive samples with a 99.33% match to RT-PCR results. It is not surprising that TSP also identified multiple infections from the 96 samples, whereas RT-PCR could not. Thus, TSP was able to accurately diagnose the samples which could not be identified based on single RT-PCR test. Our data demonstrated that TSP is a fast and accurate testing method for identifying multiple pathogen infections of the respiratory tract.

Advances in nucleic acid aptamer-based detection of respiratory virus and bacteria: a mini review.

Respiratory pathogens infecting the human respiratory system are characterized by their diversity, high infectivity, rapid transmission, and acute onset. Traditional detection methods are time-consuming, have low sensitivity, and lack specificity, failing to meet the needs of rapid clinical diagnosis. Nucleic acid aptamers, as an emerging and innovative detection technology, offer novel solutions with high specificity, affinity, and broad target applicability, making them particularly promising for respiratory pathogen detection. This review highlights the progress in the research and application of nucleic acid aptamers for detecting respiratory pathogens, discussing their selection, application, potential in clinical diagnosis, and future development. Notably, these aptamers can significantly enhance the sensitivity and specificity of detection when combined with detection techniques such as fluorescence, colorimetry and electrochemistry. This review offers new insights into how aptamers can address the limitations of traditional diagnostic methods and advance clinical diagnostics. It also highlights key challenges and future research directions for the clinical application of nucleic acid aptamers.

Comparison of targeted next-generation sequencing and metagenomic next-generation sequencing in the identification of pathogens in pneumonia after congenital heart surgery: a comparative diagnostic accuracy study

BackgroundThis study aimed to compare targeted next-generation sequencing (tNGS) with metagenomic next-generation sequencing (mNGS) for pathogen detection in infants with severe postoperative pneumonia after congenital heart surgery.MethodsWe conducted a retrospective observational study using data from the electronic medical record system of infants who developed severe pneumonia after surgery for congenital heart disease from August 2021 to August 2022. Infants were divided into tNGS and mNGS groups based on the pathogen detection methods. The primary outcome was the efficiency of pathogen detection, and the secondary outcomes were the timeliness and cost of each method.ResultsIn the study, 91 infants were included, with tNGS detecting pathogens in 84.6% (77/91) and mNGS in 81.3% (74/91) of cases (P = 0.55). No significant differences were found in sensitivity, specificity, PPA, and NPA between the two methods (P > 0.05). tNGS identified five strains with resistance genes, while mNGS detected one strain. Furthermore, tNGS had a faster detection time (12 vs. 24 h) and lower cost ($150 vs. $500) compared to mNGS.ConclusiontNGS offers similar sensitivity to mNGS but with greater efficiency and cost-effectiveness, making it a promising approach for respiratory pathogen detection.

Analysis of Pathogen Detection Data in 898 Pediatric Patients Hospitalized with Community-Acquired Pneumonia

Introduction: The prevalence of community-acquired pneumonia (CAP) in pediatric patients has seen significant changes following the lifting of COVID-19 restrictions. This study examines the epidemiology and pathogen detection in children hospitalized with CAP at Beijing New Century Children's Hospital throughout 2023. Objective: To analyze the pathogen detection rates and distribution characteristics among 898 pediatric CAP patients admitted during 2023, focusing on age-related and seasonal variations. Methods: This retrospective study included 898 pediatric patients diagnosed with CAP between January 1 and December 31, 2023. Respiratory pathogen detection was performed using a combination of antigen detection kits, nucleic acid testing, and bacterial culture. The data were analyzed for pathogen distribution across different age groups and seasons. Results: Of the 898 CAP cases, pathogens were detected in 703 cases (78.3%). Mycoplasma pneumoniae was the most frequently identified pathogen (44.1%), with detection rates increasing significantly with age, particularly in school-aged children. Viral pathogens were detected in 42.7% of cases, with Respiratory Syncytial Virus (32.4%) being the most prevalent. Bacterial pathogens were identified in 49.5% of cases, with Streptococcus pneumoniae (34.1%) and Haemophilus influenzae (33.0%) being the most common. Mixed infections were observed in 64.4% of cases, with a higher prevalence in older children and during the autumn and winter seasons. Conclusions: The study highlights significant age and seasonal variations in pathogen distribution among pediatric CAP patients. Mycoplasma pneumoniae was more common in older children and during autumn, while bacterial infections peaked in winter. The findings emphasize the need for age and season-specific strategies in managing pediatric CAP and suggest that comprehensive diagnostic approaches are crucial to accurately identify the causative pathogens.

Rapid Molecular Diagnostics of Pneumonia Caused by Gram-Negative Bacteria: A Clinician's Review.

With approximately half a billion events per year, lower respiratory tract infections (LRTIs) represent a major challenge for the global public health. Among LRTI cases, those caused by Gram-negative bacteria (GNB) are associated with a poorer prognostic. Standard-of-care etiologic diagnostics is lengthy and difficult to establish, with more than half of cases remaining microbiologically undocumented. Recently, syndromic molecular diagnostic panels became available, enabling simultaneous detection of tens of pathogen-related and antimicrobial-resistance genetic markers within a few hours. In this narrative review, we summarize the available data on the performance of molecular diagnostics in GNB pneumonia, highlighting the main strengths and limitations of these assays, as well as the main factors influencing their clinical utility. We searched MEDLINE and Web of Science databases for relevant English-language articles. Molecular assays have higher analytical sensitivity than cultural methods, and show good agreement with standard-of-care diagnostics regarding detection of respiratory pathogens, including GNB, and identification of frequent patterns of resistance to antibiotics. Clinical trials reported encouraging results on the usefulness of molecular assays in antibiotic stewardship. By providing early information on the presence of pathogens and their probable resistance phenotypes, these assays assist in the choice of targeted therapy, in shortening the time from sample collection to appropriate antimicrobial treatment, and in reducing unnecessary antibiotic use.

Simultaneous Detection of Multiple Respiratory Pathogens Using an Integrated Microfluidic Chip.

Respiratory pathogens pose significant challenges to public health, demanding efficient diagnostic methods. This study presents an integrated microfluidic chip for the simultaneous detection of multiple respiratory pathogens. The chip integrates magnetic bead-based nucleic acid extraction and purification, acoustic streaming-driven mixing, liquid equalization, and multiplex PCR amplification with in situ fluorescence detection. Nucleic acid extraction takes only 12 min, yielding results comparable to commercial kits. Efficient mixing of magnetic beads is achieved through a combination of designed micropillars and bubble-trapping array structures. The micropillars maintain the aqueous phase in the mixing chamber, while the bubble-trapping arrays enable stable formation of bubbles, serving as a micromixer under the acoustic field. To prevent cross-contamination, an oil-encapsulated water droplet system is incorporated throughout nucleic acid extraction and PCR amplification. This assay displays remarkable multiplex analysis capability on a single chip, enabling the simultaneous detection of 12 common respiratory pathogens with a low detection limit of 10 copies/μL. Moreover, this method demonstrates excellent practical applicability in clinical nasal samples. Compared to many microfluidic chip-based molecular biology methods, the assay exhibits comparable or superior multipathogen analysis capability, sensitivity, and speed, completing the sample-to-answer process in approximately 70 min. This integrated microfluidic device offers a promising multiplex molecular diagnosis platform for on-site simultaneous detection of multiple pathogens.

Mini-Program Enabled IoT Intelligent Molecular Diagnostic Device for Co-Detection and Spatiotemporal Mapping of Infectious Disease Pathogens.

Effective detection of infectious pathogens is crucial for disease prevention and control. We present an innovative Internet of Things (IoT) molecular diagnostic device featuring a WeChat mini-program for simultaneous detection and spatiotemporal mapping of respiratory pathogens. Leveraging social software's widespread usage, our device integrates seamlessly with WeChat, eliminating the need for app downloads and installations. Through a comprehensive detection system, including a user-friendly mini-program, a portable Point-of-Care fluorescence detector, and a diagnostic information management platform (EzDx Cloud), we demonstrate high sensitivity and specificity in detecting common respiratory viruses. Our SARS-CoV-2/H1N1 combo test kit, developed using a novel one-tube/one-step loop-mediated isothermal amplification-CRISPR method, shows remarkable performance. We address challenges in at-home nucleic acid testing by providing a cost-effective solution capable of detecting multiple pathogens simultaneously. Our system's versatility accommodates various assays operating at different temperatures and fluorescence intensities, offering significant advantages over traditional methods. Moreover, integration with EzDx Cloud facilitates disease monitoring and early warning systems, enhancing public health management. This study highlights the potential of our IoT molecular diagnostic device in revolutionizing infectious disease detection and control, with wide-ranging applications in both human and animal population.

Epidemiological study of post-pandemic pediatric common respiratory pathogens using multiplex detection

BackgroundThe burden and characteristics of respiratory viral infections in children hospitalized for acute respiratory tract infections (ARTIs) during the post-COVID-19 pandemic era are unclear. We analyzed the epidemiological and clinical characteristics of pediatric patients hospitalized with common respiratory virus infections before and after relaxation of non-pharmaceutical interventions in Hangzhou, China and evaluated the diagnostic value of the six-panel respiratory pathogen detection system.MethodsSix types of respiratory viruses were detected in respiratory samples from children with suspected ARTIs by multiplex real-time quantitative polymerase chain reaction (RT-qPCR). Changes in virus detection rates and epidemiological and clinical characteristics, obtained from electronic health records, were analyzed. Binary logistic regression was used to identify respiratory tract infections risk factors. Multiplex RT-qPCR and targeted next-generation sequencing results were compared in random samples.ResultsAmong the 11,056 pediatric samples, 3228 tested positive for one or more of six common respiratory pathogens. RSV and PIV-3 detection rates differed significantly across age groups (both P < 0.001), and were more common in younger children. PIV-1 was more common in infants, toddlers, and preschoolers than in school-age children (P < 0.001). FluB was predominantly detected in school-age children (P < 0.001). RSV-, ADV-, and PIV-1-positivity rates were higher in 2022 than in 2023. Seasonal viral patterns differed across years. RSV (OR 9.156. 95% CI 5.905–14.195) and PIV-3 (OR 1.683, 95% CI 1.133–2.501) were risk factors for lower respiratory tract infections. RSV-positivity was associated with severe pneumonia (P = 0.044). PIV-3 (OR 0.391, 95% CI 0.170–0.899), summer season (OR 1.982, 95% CI 1.117–3.519), and younger age (OR 0.938, 95% CI 0.893–0.986) influenced pneumonia severity. Multiplex RT-qPCR showed good diagnostic performance.ConclusionAfter changes in COVID-19 prevention and control strategies, six common respiratory viruses in children were prevalent in 2022–2023, with different seasonal epidemic characteristics and age proclivities. RSV and PIV-3 cause lower, and FluA, FluB, and ADV more typically cause upper respiratory tract infections. Infancy and summer season influence severe pneumonia risk. Multiplex RT-qPCR is valuable for accurate and timely detection of respiratory viruses in children, which facilitates management, treatment, and prevention of ARTIs.

Evaluation of the FPMC respiratory panel for detection of respiratory tract pathogens in nasopharyngeal swab and sputum specimens

ObjectivesThe performance of the new Respiratory Pathogen panel (fluorescent probe melting curve, FPMC) for the qualitative detection of 12 organisms (chlamydia pneumoniae, mycoplasma pneumoniae, adenovirus, influenza A virus, influenza B virus, parainfluenza virus, rhinovirus, etc.) was assessed.MethodsProspectively collected nasopharyngeal swab (NPS) and sputum specimens (n = 635) were detected by using the FPMC panel, with the Sanger sequencing method as the comparative method.ResultsThe overall percent concordance between the FPMC analysis method and the Sanger sequencing method was 100% and 99.66% for NPS and sputum specimens, respectively. The FPMC testified an overall positive percent concordance of 100% for both NPS and sputum specimens. The FPMC analysis method also testified an overall negative percent concordance of 100% and 99.38% for NPS and sputum specimens, respectively.ConclusionsThe FPMC analysis method is a stable and accurate assay for rapid, comprehensive detecting for respiratory pathogens.

Molecular Detection of Chlamydia pneumoniae, Haemophilus influenza, and Streptococcus pneumoniae and Expression of miR-146, miR-16, and miR-221 in Patients with Chronic Obstructive Pulmonary Diseases

Abstract Background: Chronic obstructive pulmonary disease (COPD) is a debilitating respiratory condition characterized by persistent airflow limitation and chronic inflammation. Microbial infections and dysregulated microribonucleic acid (miRNA) expression have been implicated in COPD pathogenesis. This study aimed to investigate the molecular detection of three respiratory pathogens, Chlamydia pneumoniae, Haemophilus influenzae, and Streptococcus pneumoniae, in the respiratory secretions of COPD patients. In addition, it evaluated the expression levels of miR-146, miR-16, and miR-221 in the peripheral blood of COPD patients. Methods: Peripheral blood and respiratory secretions were collected from 40 healthy individuals and 40 COPD patients. The messenger ribonucleic acid expression levels of miR-146, miR-16, and miR-221 were determined using real-time polymerase chain reaction. Statistical analyses, including t-test, binomial test, and Pearson correlation, were performed. Results: H. influenzae, S. pneumoniae, and C. pneumoniae were detected in the sputum of 12.5%, 17.5%, and 7.5% of COPD patients, respectively. The expression of miR-146, miR-221, and miR-16 was observed in 65%, 15%, and 85% of COPD patients, respectively, compared to 13%, 80%, and 15% of healthy subjects. While miR-221 was downregulated in COPD patients, miR-16 and miR-146 were upregulated. No significant differences were found in the expression of these miRNAs between infected and noninfected COPD patients. Conclusion: The molecular detection of respiratory pathogens and the expression profiles of miR-146, miR-16, and miR-221 in COPD patients may have potential diagnostic value. Further research is needed to elucidate the role of these markers in COPD pathogenesis.

245 Detection of human respiratory pathogens in air and surface samples collected in several workplaces and public spaces

245 Detection of human respiratory pathogens in air and surface samples collected in several workplaces and public spaces

Palm Multidiagnostic of Mycoplasma pneumoniae, Chlamydia pneumoniae, Haemophilus influenzae, and Streptococcus pneumoniae Using One-Tube CRISPR/Cas12a

The recent high incidence of Mycoplasma pneumoniae (Mp) infections has raised widespread public health concerns. Therefore, rapid and accurate diagnosis of respiratory pathogenic microbial infections is of paramount importance to provide clinicians with accurate diagnostic insights and guide clinical medication. In response to this urgent need, we developed a one-tube Palm CRISPR/Cas12a Diagnostic (PaCD) method. This method facilitates the rapid detection of Mp infections, as well as three other prevalent respiratory pathogens, Chlamydia pneumoniae (Cp), Haemophilus influenzae (Hi), and Streptococcus pneumoniae (SP). In addition, 3D printing was employed to fabricate a compact detection device that includes a temperature control module set at 39°C and a blue light irradiation module, significantly enhancing the feasibility of point-of-care testing. The PaCD diagnostic process takes only 30 min with a detection limit of 50 copies/test, making it suitable for analysis of sputum and throat swab samples. PaCD demonstrated 100% concordance (72/72) with next-generation sequencing and exhibited high concordance with computed tomography test results. These findings demonstrate the clinical feasibility of PaCD for the rapid and accurate diagnosis of infections caused by four prevalent respiratory pathogens, offering theoretical insights into the versatile application of point-of-care tests for the detection of other respiratory pathogens in various clinical scenarios.

Evaluation of the QIAstat-Dx Respiratory SARS-CoV-2 Panel for detection of pathogens in nasopharyngeal and lower respiratory tract specimens

This study evaluates the performance of the QIAstat-Dx Respiratory SARS-CoV-2 Panel (RS2P) for the detection of respiratory pathogens. RS2P testing was performed on 440 specimens, including 82 negatives and 358 specimens positive for 1 or more targets (520 targets initially detected). Initial testing was performed on multiple platforms during routine laboratory workflow. Specimens with discordant results on RS2P were re-tested on a different platform to obtain a consensus result based on agreement of 2/3 assays. Percent positive, negative and overall agreement (PPA, PNA, POA), as well as concordance by number of targets and CT value range were calculated. RS2P produced valid results in 439 specimens, with a POA of 91.5 % based on consensus results, with 16/31 (51.6 %) discordant specimens with >1 positive target. When individual targets were examined, PPA, PNA and POA were 93.7 %, 99.9 % and 99.6 % compared to consensus results. Overall, RS2P performed well in detection of respiratory pathogens.