Respiratory Pathogens Research Articles

Detection of Enteroviruses in a Pediatric Oncology Patient Population

Abstract Enteroviruses are responsible for around 10 to 15 million infections and tens of thousands of hospitalizations annually. Infants, children, and people with weakened immune systems are more likely to get hospitalized and can have serious complications from enterovirus infection. Non-polio enteroviruses like EV-D68 can cause mild to severe symptoms like wheezing, difficulty breathing and acute flaccid myelitis (AFM). Therefore, it is crucial to continue to monitor the prevalence of enteroviruses, especially those that can potentially cause severe symptoms like EV-D68. This study focused on determining the prevalence of enteroviruses in a pediatric oncology patient population. Residual Nasopharyngeal swabs (NPS) specimens, collected from pediatric patients (<18 years old) presenting to a cancer hospital in New York between September 2022 and December 2022, and September 2023 and December 2023 for cancer care were included in the study. Rhinovirus/Enterovirus (RV/EV) was detected using the BioFire FilmArray Respiratory Panel (bioMerieux, Inc.) or the ePlex Respiratory Pathogen Panel (GenMark/Roche Molecular). For Enterovirus identification, RNA was extracted from the RV/EV positive NPS using the KingFisher™ Flex Magnetic Particle Processors (Thermo Scientific, USA), followed by RT-PCR in the ABI 7500 Fast real-time PCR instrument (ThermoFisher, USA) for enteroviruses and EV-D68 using pan-Enterovirus and EV-D68 specific primers, respectively. A total of 880 and 694 NPS samples from patients <18 years old were tested during the study period in 2022 and 2023, respectively. Of these, 238 (238/880; 27%) and 225 (225/694; 32%) RV/EV positives NPS were detected in 2022 and 2023 respectively. A total of 370 (370/463; 80%) RV/EV positive samples (182 samples from 2022 and 188 samples from 2023) were selected for additional testing and 14 samples (14/370; 4%) were positive for Enteroviruses. Of note, EV-D68 was not detected. In this study, we report a high prevalence of RV/EV which is consistent with the higher detection rate in the fall seasons, when our samples were collected. The low prevalence of EV suggests a high prevalence of RV, although this was not tested. Despite a nationwide surge in the USA in 2022, there was no EV-D68 circulating in these patients. Further analysis, using Whole genome sequencing of the enteroviruses detected in this study will provide additional information on specific circulating Enterovirus genotypes.

Regulation of Airway Epithelial-Derived Alarmins in Asthma: Perspectives for Therapeutic Targets.

Asthma is a chronic respiratory condition predominantly driven by a type 2 immune response. Epithelial-derived alarmins such as thymic stromal lymphopoietin (TSLP), interleukin (IL)-33, and IL-25 orchestrate the activation of downstream Th2 cells and group 2 innate lymphoid cells (ILC2s), along with other immune effector cells. While these alarmins are produced in response to inhaled triggers, such as allergens, respiratory pathogens or particulate matter, disproportionate alarmin production by airway epithelial cells can lead to asthma exacerbations. With alarmins produced upstream of the type 2 inflammatory cascade, understanding the pathways by which these alarmins are regulated and expressed is critical to further explore new therapeutics for the treatment of asthmatic patients. This review emphasizes the critical role of airway epithelium and epithelial-derived alarmins in asthma pathogenesis and highlights the potential of targeting alarmins as a promising therapeutic to improve outcomes for asthma patients.

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.

Investigation of the Effect of the COVID-19 Pandemic Period on Respiratory Tract Viruses at Istanbul Medical Faculty Hospital, Turkey.

Aim: Respiratory viruses significantly impact public health, contributing to high morbidity and mortality rates in both children and adults. This study evaluates the distribution and incidence of respiratory tract viruses in our hospital from 2019 to 2022, focusing on changes post-COVID-19 pandemic. Material and Methods: Utilizing molecular methods, we analyzed nasopharyngeal swabs with the FTD Respiratory Pathogens 21 kit and the QIAStat Dx Respiratory Panel kit at Istanbul Faculty of Medicine. A total of 1186 viruses were detected in 2488 samples (47.6% of the total) examined with the FTD Respiratory Pathogens 21 kit between 2019 and 2022. Results: It was determined that the detection rates were 52.8% in 2019, 44.3% in 2020, 50.0% in 2021, and 40.0% in 2022. Notable changes in prevalence were observed for pandemic influenza A (IAV-H1N1pdm2009), parainfluenza virus (PIV)-3, rhinovirus (RV), and respiratory syncytial virus (RSV)-A/B (p < 0.05). RV consistently showed the highest detection rates across all years (17.6% to 7.9%). Additionally, 1276 viruses were detected in 1496 samples using the QIAStat DX kit, with 91.3% positivity in 2021 and 78.6% in 2022, highlighting the kit's effectiveness in rapid diagnosis. Conclusions: This study enhances understanding of respiratory virus epidemiology during and after the pandemic, emphasizing the need for ongoing surveillance and strategic public health measures to address the evolving landscape of respiratory infections.

Phytochemistry, Mechanisms, and Preclinical Studies of Echinacea Extracts in Modulating Immune Responses to Bacterial and Viral Infections: A Comprehensive Review.

Echinacea species, particularly Echinacea purpurea, Echinacea angustifolia, and Echinacea pallida, are renowned for their immunomodulatory, antibacterial, and antiviral properties. This review explores the mechanisms by which echinacea herbal extracts modulate immune responses, focusing on their effects on both innate and adaptive immunity in bacterial and viral infections. Key bioactive compounds, such as alkamides, caffeic acid derivatives, flavonoids, and polysaccharides, contribute to these effects. These compounds enhance immune cell activity, including macrophages and natural killer cells, stimulating cytokine production and phagocytosis. The antibacterial activity of echinacea against respiratory pathogens (Streptococcus pneumoniae, Haemophilus influenzae, Legionella pneumophila) and skin pathogens (Staphylococcus aureus, Propionibacterium acnes) is reviewed, as well as its antiviral efficacy against viruses like herpes simplex, influenza, and rhinovirus. Echinacea's potential as a complementary treatment alongside conventional antibiotics and antivirals is discussed, particularly in the context of antibiotic resistance and emerging viral threats. Challenges associated with variability in phytochemical content and the need for standardized extraction processes are also addressed. This review provides a comprehensive overview of echinacea's therapeutic potential and outlines future directions for research, including clinical trials and dosage optimization.

Respiratory pathogen analysis in pediatric inpatients unraveled the infection pattern of Mycoplasma pneumoniae post the COVID-19 pandemic.

To counteract the COVID-19 pandemic, nonpharmaceutical interventions (NPIs) were implemented globally, exerting a profound influence on a wide spectrum of infectious diseases, encompassing respiratory tract infections (RTIs). Subsequent to the easing of NPIs, China experienced a significant outbreak of Mycoplasma pneumoniae (MP). Over a decade from 2015 to 2024, our study scrutinized 12 common infectious diseases among pediatric children. Etiologically diagnostic data and clinical outcome metrics of children with RTIs, tested for 13 pathogens, were analyzed to evaluate changes during and after the pandemic compared to pre-pandemic periods, with a notable emphasis on age profile and coinfection patterns of MP. Among 57,471 hospitalized children, 23,178 were diagnosed with infectious diseases. Under NPIs, most respiratory infections declined compared to pre-pandemic levels, rebounding by 69.64% in 2023. While the infection rate of common respiratory pathogens decreased, cases of respiratory syncytial virus increased during the period of extensive NPI implementation. In 2023, pediatric intensive care unit durations for these pathogens increased, suggesting greater severity of illness compared to 2019. MP exhibited the highest infection rate (31.38% average), with a notable outbreak post-pandemic due to severity increase in <3 year olds and rise among older children. NPIs reduced MP coinfections and mitigated their severity, while exerting a significant influence on bacterial coinfections with MP over the span of 5 years, in contrast to their impact on viral pathogens. NPIs effectively curb transmission of respiratory infections by most pathogens, resulting in increased average age of MP infections and altered patterns of coinfection post-pandemic.

Forecasting severe respiratory disease hospitalizations using machine learning algorithms

BackgroundForecasting models predicting trends in hospitalization rates have the potential to inform hospital management during seasonal epidemics of respiratory diseases and the associated surges caused by acute hospital admissions. Hospital bed requirements for elective surgery could be better planned if it were possible to foresee upcoming peaks in severe respiratory illness admissions. Forecasting models can also guide the use of intervention strategies to decrease the spread of respiratory pathogens and thus prevent local health system overload. In this study, we explore the capability of forecasting models to predict the number of hospital admissions in Auckland, New Zealand, within a three-week time horizon. Furthermore, we evaluate probabilistic forecasts and the impact on model performance when integrating laboratory data describing the circulation of respiratory viruses.MethodsThe dataset used for this exploration results from active hospital surveillance, in which the World Health Organization Severe Acute Respiratory Infection (SARI) case definition was consistently used. This research nurse-led surveillance has been implemented in two public hospitals in Auckland and provides a systematic laboratory testing of SARI patients for nine respiratory viruses, including influenza, respiratory syncytial virus, and rhinovirus. The forecasting strategies used comprise automatic machine learning, one of the most recent generative pre-trained transformers, and established artificial neural network algorithms capable of univariate and multivariate forecasting.ResultsWe found that machine learning models compute more accurate forecasts in comparison to naïve seasonal models. Furthermore, we analyzed the impact of reducing the temporal resolution of forecasts, which decreased the model error of point forecasts and made probabilistic forecasting more reliable. An additional analysis that used the laboratory data revealed strong season-to-season variations in the incidence of respiratory viruses and how this correlates with total hospitalization cases. These variations could explain why it was not possible to improve forecasts by integrating this data.ConclusionsActive SARI surveillance and consistent data collection over time enable these data to be used to predict hospital bed utilization. These findings show the potential of machine learning as support for informing systems for proactive hospital management.

Evaluation of the Seegene Allplex™ RV master assay for one-step simultaneous detection of eight respiratory viruses in nasopharyngeal specimens

BackgroundThe Seegene Allplex™ RV Master (RVM) assay is a one-step multiplex real-time reverse transcription polymerase chain reaction (RT-PCR) system for detecting eight viral respiratory pathogens from nasopharyngeal swab, aspirate, and bronchoalveolar lavage specimens. The eight RVM targets are: severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Influenza A (Flu A), Influenza B (Flu B), Human respiratory syncytial virus (RSV), adenovirus (AdV), rhinovirus (HRV), parainfluenza virus (PIV), and metapneumovirus (MPV). The assay is based on Seegene’s multiple detection temperature (MuDT) technology and provides cycle threshold (Ct) values for each of its viral targets upon PCR completion. ObjectiveWe aimed to evaluate the diagnostic performance of the RVM assay by calculating sensitivity, specificity, accuracy, Positive Predictive Value (PPV), Negative Predictive Value (NPV), Positive Percent Agreement (PPA), Negative Percent Agreement (NPA), and Overall Percent Agreement (OPA) compared to definite diagnosis and analogous reference assays. Study designDiagnostic sensitivity, specificity, accuracy, PPV, and NPV were calculated by comparing the results of the RVM assay to that of definite diagnosis assays; while PPA, NPA, and OPA were calculated by comparing results of the RVM assay to that of analogous reference products. Definite diagnosis and reference methods comprised whole genome sequencing and PCR genotyping, the Allplex™ SARS-CoV-2/FluA/FluB/RSV and Respiratory Panels 1, 2, and 3 assays (Seegene), and the Xpert® Xpress SARS-CoV-2/FluA/FluB/RSV Plus assay (Cepheid). Reproducibility of the RVM assay using fully-automated and semi-automated nucleic acid (NA) extraction workflows and as performed by independent operators was also assessed. In total, 249 positive respiratory specimens and at least 50 negative specimens for each target tested were used for this evaluation study. ResultsSensitivity, specificity, accuracy, PPV, NPV, PPA, NPA, and OPA ranged from 95.7 % to 100 % for detecting all eight targets tested on the RVM assay. Reproducibility PPA, NPA, and OPA between automated and semi-automated NA extraction workflows were all >97.9 %, while the reproducibility PPA, NPA and OPA between independent operators were all 100 %. ConclusionThese results demonstrate a high level of sensitivity, specificity, accuracy and diagnostic predictive value of the RVM assay and high agreement with comparable reference assays in identifying all eight of its targets. Taken together, our study underscores the diagnostic utility of the RVM assay in detecting eight viral respiratory pathogens.

Mannose and Lactobionic Acid in Nasal Vaccination: Enhancing Antigen Delivery via C-Type Lectin Receptors.

Nasal vaccines are a promising strategy for enhancing mucosal immune responses and preventing diseases at mucosal sites by stimulating the secretion of secretory IgA, which is crucial for early pathogen neutralization. However, designing effective nasal vaccines is challenging due to the complex immunological mechanisms in the nasal mucosa, which must balance protection and tolerance against constant exposure to inhaled pathogens. The nasal route also presents unique formulation and delivery hurdles, such as the mucous layer hindering antigen penetration and immune cell access. This review focuses on cutting-edge approaches to enhance nasal vaccine delivery, particularly those targeting C-type lectin receptors (CLRs) like the mannose receptor and macrophage galactose-type lectin (MGL) receptor. It elucidates the roles of these receptors in antigen recognition and uptake by antigen-presenting cells (APCs), providing insights into optimizing vaccine delivery. While a comprehensive examination of targeted glycoconjugate vaccine development is outside the scope of this study, we provide key examples of glycan-based ligands, such as lactobionic acid and mannose, which can selectively target CLRs in the nasal mucosa. With the rise of new viral infections, this review aims to facilitate the design of innovative vaccines and equip researchers, clinicians, and vaccine developers with the knowledge to enhance immune defenses against respiratory pathogens, ultimately protecting public health.

A review of clinical and preclinical data supporting a role for resveratrol in the treatment of common respiratory tract pathogens

Respiratory infections are a relevant issue during infancy and childhood, constituting a major source of morbidity and imposing a substantial burden on healthcare systems. Conditions such as bronchiolitis, pneumonia, and influenza exemplify the gravity of these infections among pediatric populations. In the context of this health challenge, resveratrol, a naturally occurring polyphenolic antioxidant has emerged as a focal point of extensive research, known for its antioxidant, anti-inflammatory, and antimicrobial properties. This comprehensive review delves into the compound's extensive antimicrobial activities against a diverse range of bacteria and viruses, both as a standalone agent and in combination with conventional antibiotics. This compound exhibits notable antiviral activity against viruses implicated in severe respiratory infections, offering a potential therapeutic avenue. By exploring the antiviral mechanisms and highlighting the anti-inflammatory potential of resveratrol, this comprehensive overview contributes to a deeper understanding of its applicability in mitigating the complexities associated with pediatric respiratory infections.

Molecular epidemiology of avian influenza viruses and avian coronaviruses in environmental samples from migratory bird inhabitants in Bangladesh.

Migratory birds are a natural reservoir for major respiratory viruses such as the avian influenza virus (AIV) and the avian coronavirus (AvCoV). Transmission of these viruses from migratory birds to domestic birds increases the prevalence of those diseases that cause severe economic and public health concerns in Bangladesh. The study focused on active surveillance of major respiratory viral pathogens in migratory birds, molecular identification of the viruses, and their phylogenetic origin. To conduct this study, 850 environmental samples (830 fecal samples, 10 soil samples, and 10 water samples) were collected during three consecutive winter seasons from three divisions (Dhaka, Sylhet, and Mymensingh) and pooled according to the year of collection and locations, resulting in a total of 184 tested samples. Using gene-specific primers and probes in TaqMan-and SYBR Green-based RT-qPCR assays, the samples were screened for AIV and AvCoV, respectively. Out of the 184 pooled samples, 37 were found to be positive for these respiratory pathogens. Furthermore, out of the 37 (20.11%) positive respiratory pathogens, 11.96% were AIV (n = 22) and 8.15% were AvCoV (n = 15). For the first time in Bangladesh, AIV H4N2, H4N6, and AvCoVs have been found in fecal samples from migratory birds through surveillance. Phylogenetic analyses of the HA and NA genes of AIV and the polymerase gene (Orf 1) of AvCoV revealed that these strains share a close phylogenetic relationship with the isolates from wild birds in Europe and Asia. The Bangladeshi strains with Eurasian ancestry might pose a significant threat to migratory birds flying through the Asian flyways. They might also be a potential source of virus introduction and spread to poultry raised on land. These findings emphasize the significance of ongoing AIV and AvCoV surveillance in migratory birds in Bangladesh.

Monitoring of Respiratory Disease Patterns in a Multimicrobially Infected Pig Population Using Artificial Intelligence and Aggregate Samples

A 24/7 AI sound-based coughing monitoring system was applied in combination with oral fluids (OFs) and bioaerosol (AS)-based screening for respiratory pathogens in a conventional pig nursery. The objective was to assess the additional value of the AI to identify disease patterns in association with molecular diagnostics to gain information on the etiology of respiratory distress in a multimicrobially infected pig population. Respiratory distress was measured 24/7 by the AI and compared to human observations. Screening for swine influenza A virus (swIAV), porcine reproductive and respiratory disease virus (PRRSV), Mycoplasma (M.) hyopneumoniae, Actinobacillus (A.) pleuropneumoniae, and porcine circovirus 2 (PCV2) was conducted using qPCR. Except for M. hyopneumoniae, all of the investigated pathogens were detected within the study period. High swIAV-RNA loads in OFs and AS were significantly associated with a decrease in respiratory health, expressed by a respiratory health score calculated by the AI The odds of detecting PRRSV or A. pleuropneumoniae were significantly higher for OFs compared to AS. qPCR examinations of OFs revealed significantly lower Ct-values for swIAV and A. pleuropneumoniae compared to AS. In addition to acting as an early warning system, AI gained respiratory health data combined with laboratory diagnostics, can indicate the etiology of respiratory distress.

New Insights into the Epidemiological Characteristics of Mycoplasma pneumoniae Infection before and after the COVID-19 Pandemic.

Mycoplasma pneumoniae (M. pneumoniae), a prevalent respiratory pathogen affecting children and adolescents, is known to trigger periodic global epidemics. The most recent significant outbreak commenced in the first half of 2023 and reached its peak globally during the autumn and winter months. Considering the worldwide repercussions of the COVID-19 pandemic, it has become increasingly essential to delve into the epidemiological characteristics of M. pneumoniae both before and after the pandemic. This review aims to provide a comprehensive analysis of the key features of M. pneumoniae epidemics in the pre-and post-COVID-19 contexts, including but not limited to shifts in the susceptible population, the molecular genotypes of the pathogen, the clinical manifestations, and potential new trends in drug resistance. Additionally, we will introduce the latest advancements in the diagnosis of M. pneumoniae.

Establishment of a Raman nanosphere based immunochromatographic system for the combined detection of influenza A and B viruses’ antigens on a single T-line

A simple and rapid system based on Raman nanosphere (R-Sphere) immunochromatography was developed in this study for the simultaneous detection of Influenza A, B virus antigens on a single test line (T-line). Two types of R-Sphere with different characteristic Raman spectrum were used as the signal source, which were labeled with monoclonal antibodies against FluA, FluB (tracer antibodies), respectively. A mixture of antibodies containing anti-FluA monoclonal antibody and anti-FluB monoclonal antibody (capture antibody) was sprayed on a single T-line and goat anti-chicken IgY antibody was coated as a C-line, and the antigen solution with known concentration was detected by the strip of lateral flow immunochromatography based on surface-enhanced Raman spectroscopy (SERS). The T-line was scanned with a Raman spectrometer and SERS signals were collected. Simultaneous specific recognition and detection of FluA and FluB were achieved on a single T-line by analyzing the SERS signals. The findings indicated that the test system could identify FluA and FluB in a qualitative manner in just 15 minutes, with a minimum detection threshold of 0.25 ng ml-1, excellent consistency, and specificity. There was no interference with the other four respiratory pathogens, and it exhibited 8 times greater sensitivity compared to the colloidal gold test strip method. The assay system is rapid, sensitive, and does not require repetitive sample pretreatment steps and two viruses can be detected simultaneously on a single T-line by titrating one sample, which improves detection efficiency, and provide a reference for developing multiplexed detection techniques for other respiratory viruses.

Impact of COVID-19 health precautions on asymptomatic Streptococcus pyogenes carriage in palestinian children: a pre- and post-pandemic study

BackgroundStreptococcus pyogenes (Group A Streptococcus, GAS) is a significant pathogen that causes diverse infections, ranging from pharyngitis to severe invasive diseases. Asymptomatic carriage in children is pivotal for transmission. The COVID-19 pandemic’s health measures, including mask wearing and enhanced hand hygiene, likely influenced GAS transmission dynamics. This study evaluated the impact of these precautions on the prevalence of asymptomatic pharyngeal GAS carriage among schoolchildren in the southern West Bank, Palestine.MethodsThis cross-sectional study was conducted in two phases: pre-COVID-19 (November 2019–January 2020) and post-COVID-19 (November 2023–April 2024). Throat swabs were collected from 701 children (345 pre-COVID-19, 356 post-COVID-19) via cluster sampling. The samples were tested with the ABON Strep A rapid test and confirmed by culture. Sociodemographic, health, and household data were also collected. The statistical analyses included descriptive statistics, chi-square tests, and binary logistic regression.ResultsThe prevalence of asymptomatic pharyngeal GAS carriage declined from 15.7% pre-COVID-19 to 10.4% post-COVID-19 (p = 0.038). Significant reductions were observed among urban residents (23.5–10.1%, p = 0.003) and those from medium socioeconomic backgrounds (16.0–9.1%, p = 0.008). Compared with urban residents, rural residents had lower GAS carriage rates (adjusted OR = 0.505, p = 0.023). Carriage rates also decreased among children with frequent sore throats (17.6–7.3%, p = 0.007) and those using private wells (52.5–14.9%, p < 0.001). Higher BMI was a significant risk factor (adjusted OR = 17.68, p < 0.001), whereas frequent tooth brushing (adjusted OR = 0.055, p < 0.001) and hand washing (adjusted OR = 0.367, p < 0.001) were protective factors.ConclusionsCOVID-19-related health precautions were correlated with a significant reduction in asymptomatic GAS carriage among Palestinian children. These findings suggest that public health measures, such as mask wearing and hand hygiene, can influence the transmission of respiratory pathogens. Ongoing surveillance and targeted interventions are essential for managing GAS infections, particularly in resource-limited settings.

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-287 Mycoplasma pneumoniae outbreak in 2023: Post pandemic resurgence of an atypical bacterial pathogen

Abstract Background Mycoplasma pnuemoniae is an atypical fastidious bacteria known to cause respiratory infections of both upper and lower tract, with a wide range of clinical presentations. M. pnuemoniae is one of the major causes of community acquired pneumonias worldwide. Almost all of the M pnuemoniae outbreak incidences have been reported in closed- community or congregate settings, such as schools, universities and colleges, and hospitals and long-term care facilities. Since the clinical symptoms of M pneumoniae overlap with other pneumonia causing pathogens, detection via multiplex PCR remains paramount for accurate and timely diagnosis to curb the infection spread. In the present study we demonstrate an unexpected increase in the detection of M. pneumoniae in the outpatient population, during 2023, as compared to the previous two years. In addition, a detailed analysis of the ICD10 diagnostic codes associated with the outbreak is also presented. Methods Respiratory samples (oropharyngeal, nasopharyngeal, sputum and EBL) summited to the HealthTrackRX laboratories were tested for the presence of M. pneumoniae and other respiratory bacterial and viral pathogens using the nanofluidic OpenArray qPCR platform (ThermoFisher, California, USA). Patient data was analyzed on the basis of age, gender and geographical location. Data was also classified in the basis of ICD10 diagnostic codes associated with the patient samples. All statistical analysis was performed using R version 3.6.0 (R Foundation for Statistical Computing). Results A total of 541,267 samples were submitted for testing at the HealthTrackRX facilities between January 1, 2021 and December 31, 2023. Only 13 samples tested positive for M. pneumoniae between 2021 (0.004%, n =3/61,498) and 2022 (0.006%, n = 10/165,423). The positivity rate of M. pneumoniae in 2023 increased to 0.19% (n = 621/314,346). The highest proportion of M. pneumoniae cases were detected from Georgia (26.8%), followed by Ohio (21.7%), Texas (8.5%) and California (6.4%). Most of the outbreak appears to be concentrated in large urban settings. Median age of the patients testing positive for M. pneumoniae was 10 (interquartile range [IQR] 8-18) years. Gender classification of the positive samples showed an almost equal distribution between females (49.8%) and males (50.1%). Co-infecting pathogens detected in samples positive for M. pneumoniae were similar in proportion to the M. pneumoniae negative population. The co-detected pathogens at a statistically significant difference were lower than the negative population. Survey of the ICD-10 codes submitted in conjunction with the samples suggest that the current outbreak is mostly associated with upper respiratory tract infections. Conclusions The present study shows an unprecedented increase in the detection of M. pneumoniae in the outpatient population in the United States during 2023. Our analysis suggests that this outbreak was not associated with any other bacterial or viral respiratory pathogen but appears to be case of “immunity debt” caused by the COVID19 pandemic. The outbreak of this atypical pathogen was concentrated in the pediatric population in large urban areas. Our study highlights the importance of performing continuous surveillance of respiratory pathogens, especially in the altered epidemiological landscape of the post COVID world.

A-272 Evaluation of a Real-Time Multiplex Polymerase Chain Reaction Assay for Simultaneous Detection of Respiratory Pathogens in Nasopharyngeal Specimens

Abstract Background Respiratory infections present a significant challenge due to the diverse range of pathogens involved and the possibility of concurrent infections, emphasizing the importance of rapid and accurate detection for effective treatment. Advancements in molecular methods have provided cost-effective and reliable solutions for the identification of respiratory pathogens. In this study, we aimed to assess performance characteristics of the Seegene Allplex™ 2019-nCoV Assay and Seegene Novaplex™ Respiratory Panel Assays for simultaneous amplification and detection of 22 respiratory pathogens using real-time multiplex polymerase chain reaction (PCR). Methods Nucleic acid extraction was performed using the MagMAX™ Viral/Pathogen Nucleic Acid Isolation Kit (Thermo Fisher Scientific, MA) on the CyBio® FeliX liquid handler (Analytik Jena, Germany). PCR amplification and detection were performed using the Seegene Novaplex™ Respiratory Panels 1A, 2, 3, PneumoBacter Assay, and Allplex™ 2019-nCoV Assay (Seegene Inc, South Korea) on the CFX96™ System (Bio-Rad Laboratories, CA). The assays utilize Seegene MuDT™ technology that allows for the detection of multiple targets in a single channel without the need for melt curve analysis. For method validation, precision studies were performed within-run and over 4 days. The limit of detection was verified by using plasmids from Seegene containing the target sequence for each pathogen at known concentrations. Method comparison studies were carried out by extracting and analyzing a range of 41 to 79 split samples for each pathogen against the BioFire® Respiratory 2.1 Panel (bioMérieux, France), cobas® Influenza A/B &amp; RSV Assay on the cobas® liat system (Roche Diagnostics, IN), and Lyra® SARS-CoV-2 Assay (Quidel, CA) on the CFX96™ system. Additional accuracy studies were performed by spiking negative patient samples with standards from ZeptoMetrix® (Antylia Scientific, IL) containing known concentrations of the targeted respiratory pathogens. Results Precision studies demonstrated consistent and reproducible results for all pathogens. The limit of detection was verified at 1000 copies/reaction for human parainfluenza virus 4 and human metapneumovirus, and at 100 copies/reaction for all other pathogens. Results of the spike-and-recovery studies were consistent with expected results for all targets. Patient correlation studies showed 100% agreement with expected pathogen identification for 19 pathogens, and greater than 97.9% agreement for influenza B virus, respiratory syncytial virus, human parainfluenza virus 4, and human coronavirus 229E. Conclusions The Seegene Allplex™ 2019-nCoV Assay and Novaplex™ Respiratory Panel Assays offer a rapid and reliable method for detecting respiratory pathogens in nasopharyngeal specimens. The capability of the assays to detect multiple targets in a single well enhances efficiency, cost-effectiveness, and turnaround time.

B-201 Clinical Performance Evaluation of IRON-qPCR™ RV, a Novel Molecular POCT system, for the Qualitative Detection of Respiratory Viruses in Nasopharyngeal Swab

Abstract Background The availability of Point-of-Care testing (POCT) based on molecular diagnostics to test simultaneously for multiple respiratory viruses is very limited though significant progress has been made in molecular testing for COVID-19 during the pandemic. Considering the similar symptoms presented by patients infected with various respiratory pathogens, it is crucial to have multiple POCT systems capable of detecting multiple respiratory pathogens while distinguishing SARS-CoV-2 from other pathogens. To meet the growing demand for multiplex testing for respiratory pathogens, a molecular POCT, IRON-qPCR™ RV has been developed. IRfON-qPCR™ RV is a multiplex real-time RT-PCR assay designed for the qualitative detection and differentiation of SARS-CoV-2, Influenza A, Influenza B, RSV-A, and RSV-B RNA from human nasopharyngeal swab specimens. The IRON-qPCR™ proceeds the entire process automatically from nucleic acid extraction to real-time RT-PCR within 40 minutes. The main goal of this study is to evaluate the clinical performance of IRON-qPCR™ RV in comparison with other assays and kits using nasopharyngeal swab samples. Methods To assess the clinical performance of the IRON-qPCR™ RV, specimen collection and evaluation were conducted at a clinical institution in France, utilizing a total of 980 nasopharyngeal swab samples. The comparators used were the Xpert® Xpress CoV-2/Flu/RSV plus Kit and the RealStar® RSV RT-PCR Kit 3.0. Since RSV subtypes are not distinguished by the Xpert kit, all RSV without subtype distinction were compared. Additionally, RealStar kit was used to compare the results of IRON-qPCR™ RV for RSV subtypes A and B. Clinical samples showing discrepancies between Xpert and RealStart, and the IRON-qPCR™ RV were further analyzed using Allplex™ SARS-CoV-2/FuA/FluB/RSV Assay and sequencing. Results Through the comparison of clinical performance of the IRON-qPCR™ RV with Xpert for SARS-CoV-2, Influenza A, and Influenza B in nasopharyngeal swab samples, the clinical sensitivity was analyzed to be over 95.5%, and the clinical specificity was over 99.6%. For RSV, compared to Xpert, the clinical sensitivity was analyzed to be 96.9%, and the clinical specificity was 98.9%. Furthermore, in comparison with RealStar, the clinical sensitivity and specificity of IRON-qPCR™ RV for RSV-A were determined to be 96.2% and 100%, respectively, and the clinical sensitivity and specificity for RSV-B were 96.0% and 100%. Additionally, discrepant samples in comparison with Xpert were further tested using the Allplex as a resolver kit. The result showed that the clinical sensitivity and specificity of IRON-qPCR™ RV for SARS-CoV-2, Influenza A, and Influenza B were over 98.3% and 100%. For RSV, the clinical sensitivity and specificity were 99.5% and 99.1%. Conclusions The clinical performance of IRON-qPCR™ RV was analyzed with the clinical sensitivity of over 95% and the clinical specificity of over 99%. Upon analysis including the results of the resolver kit for discrepant samples, increased clinical sensitivity and specificity were determined. The results of this study strongly support that the IRON-qPCR™ RV is a reliable POCT system for the simultaneous detection and differentiation of multiple respiratory viruses. Furthermore, it is applicable to district hospitals as well as clinical laboratories for accurate and timely testing.

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.