Metagenomic analysis identified co-infection with human rhinovirus C and bocavirus 1 in an adult suffering from severe pneumonia

Exploring the respiratory viral landscape beyond influenza and SARS-CoV-2: a 2020-2023 study in Fujian, China

Introduction

In this study, we investigated the local epidemiology and pathogen spectrum of acute respiratory infections caused by common respiratory viruses other than influenza virus (IFV) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Fujian Province, China, from September 2020 to December 2023.

Methods

Samples negative for IFV and SARS-CoV-2 were randomly selected from individuals presenting with influenza-like illness. These samples were tested for seven common respiratory viruses-human respiratory syncytial virus (HRSV), human parainfluenza virus (HPIV), human adenovirus (HAdV), rhinovirus (RV), human metapneumovirus, human coronavirus (HCoV), and human bocavirus. Quantification fluorescence polymerase chain reaction (qPCR) was used for detection.

Results

One or more respiratory viruses were identified in 30.2% (n = 1,010/3,345) of the collected samples. RV was the most prevalent (10.9%), followed by HPIV (6.2%) and HRSV (4.5%). HPIV-3 was the dominant HPIV subtype (44.0%), and HCoV-OC43 was the predominant HCoV genotype (54.4%). Co-infections were observed in 2.9% (n = 96) of cases, with RV and HPIV co-infection being the most frequent. Age-specific variations were observed for most viruses, except for HCoV. HRSV exhibited a notably higher prevalence in young children (<5 years) and seniors (≥60 years), while HAdV was more common in children younger than 15 years. Regarding seasonal distribution, RV peaked in spring and autumn, whereas HRSV peaked in summer and autumn. No clear seasonal trends were observed for HPIV and HAdV. A negative correlation was observed between the incidence of IFV and the seven targeted respiratory viruses.

Discussion

These findings collectively underscore the importance of age-specific and seasonally tailored interventions, as well as the need for comprehensive diagnostic tools capable of simultaneously identifying multiple pathogens.

Application of the metagenomic next-generation sequencing technology to identify the causes of pleural effusion

Background

Pleural effusion (PE), frequently encountered in clinical practice, can arise from a variety of underlying conditions. Accurate differential diagnosis of PE is crucial, as treatment and prognosis are heavily dependent on the underlying etiology. However, diagnosing the cause of PE remains challenging, relying on mycobacteriological methods that lack sensitivity and are time-consuming, or on histological examinations that require invasive biopsies. The recent advancements in metagenomic next-generation sequencing (mNGS) have shown promising applications in the diagnosis of infectious diseases. Despite this, there is limited research on the utility of mNGS as a comprehensive diagnostic tool for simultaneously identifying the causes of PE, particularly in cases of tuberculosis or malignancy.

Methods

This study aimed to assess the efficacy of mNGS in detecting tuberculous pleural effusion (TPE) and malignant pleural effusion (MPE). A total of 35 patients with PE were included, and their PE samples were analyzed using mNGS.

Results

Among the participants, 8 were ultimately diagnosed with TPE, and 10 were diagnosed with MPE, with lung adenocarcinoma being the most prevalent pathological type (50%, 5/10), according to established diagnostic criteria. Additionally, 7 patients were diagnosed with non-infectious PE. However, mNGS identified only 2 cases of TPE and 8 cases of MPE. The sensitivity of mNGS for detecting Mycobacterium tuberculosis was 25% (2/8), while the specificity was 100%. For tumor detection, mNGS demonstrated a sensitivity of 80%, a specificity of 92.6%, and an AUC of 0.882.

Conclusion

mNGS is effective in distinguishing MPE from non-MPE, but is not suitable for diagnosing TPE.

Application of metagenomic next-generation sequencing in the diagnosis of infectious diseases

Metagenomic next-generation sequencing (mNGS) is a transformative approach in the diagnosis of infectious diseases, utilizing unbiased high-throughput sequencing to directly detect and characterize microbial genomes from clinical samples. This review comprehensively outlines the fundamental principles, sequencing workflow, and platforms utilized in mNGS technology. The methodological backbone involves shotgun sequencing of total nucleic acids extracted from diverse sample types, enabling simultaneous detection of bacteria, viruses, fungi, and parasites without prior knowledge of the infectious agent. Key advantages of mNGS include its capability to identify rare, novel, or unculturable pathogens, providing a more comprehensive view of microbial communities compared to traditional culture-based methods. Despite these strengths, challenges such as data analysis complexity, high cost, and the need for optimized sample preparation protocols remain significant hurdles. The application of mNGS across various systemic infections highlights its clinical utility. Case studies discussed in this review illustrate its efficacy in diagnosing respiratory tract infections, bloodstream infections, central nervous system infections, gastrointestinal infections, and others. By rapidly identifying pathogens and their genomic characteristics, mNGS facilitates timely and targeted therapeutic interventions, thereby improving patient outcomes and infection control measures. Looking ahead, the future of mNGS in infectious disease diagnostics appears promising. Advances in bioinformatics tools and sequencing technologies are anticipated to streamline data analysis, enhance sensitivity and specificity, and reduce turnaround times. Integration with clinical decision support systems promises to further optimize mNGS utilization in routine clinical practice. In conclusion, mNGS represents a paradigm shift in the field of infectious disease diagnostics, offering unparalleled insights into microbial diversity and pathogenesis. While challenges persist, ongoing technological advancements hold immense potential to consolidate mNGS as a pivotal tool in the armamentarium of modern medicine, empowering clinicians with precise, rapid, and comprehensive pathogen detection capabilities.

Factors associated with outcome in a national cohort of rhinovirus hospitalized patients in Brazil in 2022

The common cold is the primary cause of illness in the community, with over 200 viral strains identified, and rhinovirus infections being the most prevalent. Coronavirus Disease 19 (COVID-19) is also a significant cause of severe illness. The burden of acute respiratory infections has a significant impact on the economy, resulting in absenteeism from work and school. Rhinovirus infections can exacerbate asthma and other chronic diseases, leading to hospitalization. The objective of this study is to investigate the factors associated with death and survival in patients hospitalized for rhinovirus in Brazil in 2022. This is a retrospective cohort study using data from the national surveillance of Severe Acute Respiratory Syndrome (SARS) in 2022 in Brazil, with all the norrifications. We analysed and compared clinical and epidemiological factors and outcomes between survivors and deaths in patients hospitalised for rhinovirus. The absolute and relative frequencies were calculated according to the states. Bivariate analysis was performed using chi-squared test and Fisher's exact test, while multivariate analysis was performed using COX regression. Out of 8,130 cases of SARS caused by rhinovirus, 291 (3.58%) resulted in death while 7839 (96.47%) patients survived. The factors associated with death were invasive ventilation (p- < 0.001 HR 4.888 CI 95% 3.816-6.262), bocavirus (p- < 0.001 HR 4.204 CI 95% 2.595-6.812), immunodepression/Immunosuppression (p- < 0.001 HR 2.417 CI 95% 1. 544-3, 786), COVID-19 (p- < 0.001 HR 2.167 CI 95% 1.495-3.142), chronic neurological diseases (p-0.007 HR 1.610 CI 95% 1.137-2.280), abdominal pain (p-0.005 HR 1.734 CI 95% 1.186-2.537), age (p- < 0.001 HR 1.038 CI 95% 1.034-1.042). The survival factors identified in this study were dyspnea (p = 0.005; HR 0.683; CI 95% 0.524-0.889), cough (p < 0.001; HR 0.603; CI 95% 0.472-0.769), and asthma (p = 0.052; HR 0.583; CI 95% 0.339-1.004). Additionally, the study found that receiving a COVID-19 booster dose was also a significant survival factor (p = 0.001; HR 0.570; CI 95% 0.415-0.784). The factors associated with death were similar to those in the literature, and the factors associated with survival were also similar, except for the booster dose of the COVID-19 vaccine, which we didn't find in any studies. Our study is the first to associate the full course of the COVID-19 vaccine with survival in those hospitalized for rhinovirus, regardless of COVID-19 and rhinovirus co-detection.

Human bocavirus respiratory infection: Tracing the path from viral replication and virus-cell interactions to diagnostic methods

Human bocaviruses were first described between 2005 and 2010, identified in respiratory and enteric tract samples of children. Screening studies have shown worldwide distribution. Based on phylogenetic analysis, they were classified into four genotypes (HBoV1-4). From a clinical perspective, human bocavirus 1 (HBoV1) is considered the most relevant, since it can cause upper and lower acute respiratory tract infection, mainly in infants, including common cold, bronchiolitis, and pneumonia, as well as wheezing in susceptible patients. However, the specific processes leading to structural, biochemical, and functional changes resulting in the different clinical presentations have not been elucidated yet. This review surveys the interactions between the virus and target cells that can potentially explain disease-causing mechanisms. It also summarises the clinical phenotype of cases, stressing the role of HBoV1 as an aetiological agent of lower acute respiratory infection in infants, together with laboratory tests for detection and diagnosis. By exploring the current knowledge on the epidemiology of HBoV1, insights into the complex scenario of paediatric respiratory infections are presented, as well as the potential effects that changes in the circulation can have on the dynamics of respiratory agents, spotlighting the benefits of comprehensively increase insights into incidence, interrelationships with co-circulating agents and potential control of HBoV1.

RAPIDprep: A Simple, Fast Protocol for RNA Metagenomic Sequencing of Clinical Samples

Emerging infectious disease threats require rapid response tools to inform diagnostics, treatment, and outbreak control. RNA-based metagenomics offers this; however, most approaches are time-consuming and laborious. Here, we present a simple and fast protocol, the RAPIDprep assay, with the aim of providing a cause-agnostic laboratory diagnosis of infection within 24 h of sample collection by sequencing ribosomal RNA-depleted total RNA. The method is based on the synthesis and amplification of double-stranded cDNA followed by short-read sequencing, with minimal handling and clean-up steps to improve processing time. The approach was optimized and applied to a range of clinical respiratory samples to demonstrate diagnostic and quantitative performance. Our results showed robust depletion of both human and microbial rRNA, and library amplification across different sample types, qualities, and extraction kits using a single workflow without input nucleic-acid quantification or quality assessment. Furthermore, we demonstrated the genomic yield of both known and undiagnosed pathogens with complete genomes recovered in most cases to inform molecular epidemiological investigations and vaccine design. The RAPIDprep assay is a simple and effective tool, and representative of an important shift toward the integration of modern genomic techniques with infectious disease investigations.

Advantages and challenges of metagenomic sequencing for the diagnosis of pulmonary infectious diseases

Objective

We aim to familiarize the application status of metagenomic sequencing in diagnosing pulmonary infections, to compare metagenomic sequencing with traditional diagnostic methods, to conclude the advantages and limitations of metagenomic sequencing, and to provide some advice for clinical practice and some inspiration for associated researches.

Data Sources

The data were obtained from peer‐reviewed literature, white papers, and meeting reports.

Results

This review focused on the applications of untargeted metagenomic sequencing in lungs infected by bacteria, viruses, fungi, chlamydia pneumoniae, Mycoplasma pneumoniae, parasites, and other pathogens. Compared with conventional diagnostic methods, metagenomic sequencing is better in detecting novel, rare, and unexpected pathogens and being applied in co‐infections. Meanwhile, it can also provide more comprehensive information about pathogens. However, metagenomic sequencing still has limitations. Also, the situations that should be applied in and how the results should be interpreted are discussed in this review.

Conclusion

Metagenomic sequencing improves efficiency to identify pathogens compared with traditional diagnostic methods and can be applied in clinical diagnosis. However, the technology of metagenomic sequencing still needs to be improved. Also, clinicians should learn more about when to use metagenomic sequencing and how to interpret its results.

The Diagnostic Value of Metagenomic Next-Generation Sequencing in Lower Respiratory Tract Infection

Lower respiratory tract infections are associated with high morbidity and mortality and significant clinical harm. Due to the limited ability of traditional pathogen detection methods, anti-infective therapy is mostly empirical. Therefore, it is difficult to adopt targeted drug therapy. In recent years, metagenomic next-generation sequencing (mNGS) technology has provided a promising means for pathogen-specific diagnosis and updated the diagnostic strategy for lower respiratory tract infections. This article reviews the diagnostic value of mNGS for lower respiratory tract infections, the impact of different sampling methods on the detection efficiency of mNGS, and current technical difficulties in the clinical application of mNGS.

High-Throughput Metagenomics for Identification of Pathogens in the Clinical Settings

The application of sequencing technology is shifting from research to clinical laboratories owing to rapid technological developments and substantially reduced costs. However, although thousands of microorganisms are known to infect humans, identification of the etiological agents for many diseases remains challenging as only a small proportion of pathogens are identifiable by the current diagnostic methods. These challenges are compounded by the emergence of new pathogens. Hence, metagenomic next-generation sequencing (mNGS), an agnostic, unbiased, and comprehensive method for detection, and taxonomic characterization of microorganisms, has become an attractive strategy. Although many studies, and cases reports, have confirmed the success of mNGS in improving the diagnosis, treatment, and tracking of infectious diseases, several hurdles must still be overcome. It is, therefore, imperative that practitioners and clinicians understand both the benefits and limitations of mNGS when applying it to clinical practice. Interestingly, the emerging third-generation sequencing technologies may partially offset the disadvantages of mNGS. In this review, mainly: a) the history of sequencing technology; b) various NGS technologies, common platforms, and workflows for clinical applications; c) the application of NGS in pathogen identification; d) the global expert consensus on NGS-related methods in clinical applications; and e) challenges associated with diagnostic metagenomics are described.

Genetics and genomics of SARS-CoV-2: A review of the literature with the special focus on genetic diversity and SARS-CoV-2 genome detection

The outbreak of 2019-novel coronavirus disease (COVID-19), caused by SARS-CoV-2, started in late 2019; in a short time, it has spread rapidly all over the world. Although some possible antiviral and anti-inflammatory medications are available, thousands of people are dying daily. Well-understanding of the SARS-CoV-2 genome is not only essential for the development of new treatments/vaccines, but it also can be used for improving the sensitivity and specificity of current approaches for virus detection. Accordingly, we reviewed the most critical findings related to the genetics of the SARS-CoV-2, with a specific focus on genetic diversity and reported mutations, molecular-based diagnosis assays, using interfering RNA technology for the treatment of patients, and genetic-related vaccination strategies. Additionally, considering the unanswered questions or uncertainties in these regards, different topics were discussed.

Gemykibivirus Genome in Lower Respiratory Tract of Elderly Woman With Unexplained Acute Respiratory Distress Syndrome

Using metagenomics analysis, we are the first to identify the presence of a small, circular, single-stranded Gemykibivirus (GkV) genome from the respiratory tract of an elderly woman with severe acute respiratory distress syndrome. Our results suggest that further studies on whether GkVs infect humans and cause respiratory disease are needed.

Metagenomic Analysis Reveals Clinical SARS-CoV-2 Infection and Bacterial or Viral Superinfection and Colonization

BACKGROUND

More than 2 months separated the initial description of SARS-CoV-2 and discovery of its widespread dissemination in the United States. Despite this lengthy interval, implementation of specific quantitative reverse transcription (qRT)-PCR-based SARS-CoV-2 tests in the US has been slow, and testing is still not widely available. Metagenomic sequencing offers the promise of unbiased detection of emerging pathogens, without requiring prior knowledge of the identity of the responsible agent or its genomic sequence.

METHODS

To evaluate metagenomic approaches in the context of the current SARS-CoV-2 epidemic, laboratory-confirmed positive and negative samples from Seattle, WA were evaluated by metagenomic sequencing, with comparison to a 2019 reference genomic database created before the emergence of SARS-CoV-2.

RESULTS

Within 36 h our results showed clear identification of a novel human Betacoronavirus, closely related to known Betacoronaviruses of bats, in laboratory-proven cases of SARS-CoV-2. A subset of samples also showed superinfection or colonization with human parainfluenza virus 3 or Moraxella species, highlighting the need to test directly for SARS-CoV-2 as opposed to ruling out an infection using a viral respiratory panel. Samples negative for SARS-CoV-2 by RT-PCR were also negative by metagenomic analysis, and positive for Rhinovirus A and C. Unlike targeted SARS-CoV-2 qRT-PCR testing, metagenomic analysis of these SARS-CoV-2 negative samples identified candidate etiological agents for the patients' respiratory symptoms.

CONCLUSION

Taken together, these results demonstrate the value of metagenomic analysis in the monitoring and response to this and future viral pandemics.

mNGS in clinical microbiology laboratories: on the road to maturity

Metagenomic next-generation sequencing (mNGS) is increasingly being applied in clinical laboratories for unbiased culture-independent diagnosis. Whether it can be a next routine pathogen identification tool has become a topic of concern. We review the current implementation of this new technology for infectious disease diagnostics and discuss the feasibility of transforming mNGS into a routine diagnostic test. Since 2008, numerous studies from over 20 countries have revealed the practicality of mNGS in the work-up of undiagnosed infectious diseases. mNGS performs well in identifying rare, novel, difficult-to-detect and coinfected pathogens directly from clinical samples and presents great potential in resistance prediction by sequencing the antibiotic resistance genes, providing new diagnostic evidence that can be used to guide treatment options and improve antibiotic stewardship. Many physicians recognized mNGS as a last resort method to address clinical infection problems. Although several hurdles, such as workflow validation, quality control, method standardisation, and data interpretation, remain before mNGS can be implemented routinely in clinical laboratories, they are temporary and can be overcome by rapidly evolving technologies. With more validated workflows, lower cost and turnaround time, and simplified interpretation criteria, mNGS will be widely accepted in clinical practice. Overall, mNGS is transforming the landscape of clinical microbiology laboratories, and to ensure that it is properly utilised in clinical diagnosis, both physicians and microbiologists should have a thorough understanding of the power and limitations of this method.