Agnostic Sequencing for Detection of Viral Pathogens

Integrating multiplex PCR in fever clinics for acute respiratory pathogen-specific diagnosis

The epidemiological patterns of respiratory tract infections (RTIs) have experienced substantial changes due to the influence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with a particular focus on acute respiratory infections (ARIs). Challenges in early diagnosis, inadequate triage strategies, and the inappropriate use of antimicrobials or antivirals have compounded the difficulties in accurately diagnosing and managing ARIs in the post-pandemic context. This study aimed to investigate the efficacy of fever clinics equipped with nucleic acid testing capabilities in the precise triage of ARIs. In a cohort of 604 individuals presenting with symptoms of ARIs, we utilized real-time reverse transcription polymerase chain reaction (RT-PCR) technology available in the fever clinic to perform nucleic acid testing for SARS-CoV-2, influenza A virus (Flu A), influenza B virus (Flu B), respiratory syncytial virus, adenovirus, human rhinovirus, and Mycoplasma pneumoniae. Subsequently, statistical methods were employed to analyze the distribution and types of ARIs associated with these pathogens. In fever clinics, most patients presenting with respiratory pathogen infections were diagnosed with non-SARS-CoV-2 respiratory pathogens, with a higher incidence noted among pediatric patients compared to adults. In contrast, SARS-CoV-2 primarily affected the adult population and was linked to more severe clinical outcomes. Consequently, the swift triage of patients exhibiting ARI symptoms in a fever clinic equipped with nucleic acid testing enables the rapid identification and precise treatment of pathogens. This approach alleviates patient discomfort and enhances the efficiency of healthcare resource utilization.

Viral metagenomics reveals diverse viruses in the fecal samples of children with acute respiratory infection

Introduction

Changes in the gut microbiome have been associated with the development of acute respiratory infection (ARI). However, due to methodological limitations, our knowledge of the gut virome in patients with ARIs remains limited.

Methods

In this study, fecal samples from children with ARI were investigated using viral metagenomics.

Results

The fecal virome was analyzed, and several suspected disease-causing viruses were identified. The five viral families with the highest abundance of sequence reads were Podoviridae, Virgaviridae, Siphoviridae, Microviridae, and Myoviridae. Additionally, human adenovirus, human bocavirus, human astrovirus, norovirus, and human rhinovirus were detected. The genome sequences of these viruses were respectively described, and phylogenetic trees were constructed using the gene sequences of the viruses.

Discussion

We characterized the composition of gut virome in children with acute respiratory infections. However, further research is required to elucidate the relationship between acute respiratory infection and gut viruses.

Analytical assessment of metagenomic workflows for pathogen detection with NIST RM 8376 and two sample matrices

We assessed the analytical performance of metagenomic workflows using NIST Reference Material (RM) 8376 DNA from bacterial pathogens spiked into two simulated clinical samples: cerebrospinal fluid (CSF) and stool. Sequencing and taxonomic classification were used to generate signals for each sample and taxa of interest and to estimate the limit of detection (LOD), the linearity of response, and linear dynamic range. We found that the LODs for taxa spiked into CSF ranged from approximately 100 to 300 copy/mL, with a linearity of 0.96 to 0.99. For stool, the LODs ranged from 10 to 221 kcopy/mL, with a linearity of 0.99 to 1.01. Furthermore, discriminating different E. coli strains proved to be workflow-dependent as only one classifier:database combination of the three tested showed the ability to differentiate the two pathogenic and commensal strains. Surprisingly, when we compared the linear response of the same taxa in the two different sample types, we found those functions to be the same, despite large differences in LODs. This suggests that the "agnostic diagnostic" theory for metagenomics (i.e., any organism can be identified because DNA is the measurand) may apply to different target organisms and different sample types. Because we are using RMs, we were able to generate quantitative analytical performance metrics for each workflow and sample set, enabling relatively rapid workflow screening before employing clinical samples. This makes these RMs a useful tool that will generate data needed to support the translation of metagenomics into regulated use.IMPORTANCEAssessing the analytical performance of metagenomic workflows, especially when developing clinical diagnostics, is foundational for ensuring that the measurements underlying a diagnosis are supported by rigorous characterization. To facilitate the translation of metagenomics into clinical practice, workflows must be tested using control samples designed to probe the analytical limitations (e.g., limit of detection). Spike-ins allow developers to generate fit-for-purpose control samples for initial workflow assessments and inform decisions about further development. However, clinical sample types include a wide range of compositions and concentrations, each presenting different detection challenges. In this work, we demonstrate how spike-ins elucidate workflow performance in two highly dissimilar sample types (stool and CSF), and we provide evidence that detection of individual organisms is unaffected by background sample composition, making detection sample-agnostic within a workflow. These demonstrations and performance insights will facilitate the translation of the technology to the clinic.

A review of research progress on COF-based biosensors in pathogen detection

Despite the availability of various detection tools, the rapid identification and accurate detection of pathogens remain a major challenge in public health management. Covalent organic frameworks (COFs), which are crystalline conjugated organic polymers with considerable application potential, offer unique advantages in several fields owing to their highly ordered structure, large specific surface area, stable chemical properties, and tunable pore microenvironment. In recent years, with the rapid development of biosensing technology, COF application in the field of pathogen detection has attracted extensive attention. Herein, the properties, applications, and synthesis methods of COFs are briefly described, and the application types and basic principles of COFs in building an efficient and sensitive pathogen detection platform are emphatically discussed. Overall, we analyze the current challenges associated with COF-based biosensors in pathogen detection and look forward to their broad application prospects in biomedicine and public health in future.

Hybrid Capture-Based Sequencing Enables Highly Sensitive Zoonotic Virus Detection Within the One Health Framework

Hybrid capture-based target enrichment prior to sequencing has been shown to significantly improve the sensitivity of detection for genetic regions of interest. In the context of One Health relevant pathogen detection, we present a hybrid capture-based sequencing method that employs an optimized probe set consisting of 149,990 probes, targeting 663 viruses associated with humans and animals. The detection performance was initially assessed using viral reference materials in a background of human nucleic acids. Compared to standard metagenomic next-generation sequencing (mNGS), our method achieved substantial read enrichment, with increases ranging from 143- to 1126-fold, and enhanced detection sensitivity by lowering the limit of detection (LoD) from 103-104 copies to as few as 10 copies based on whole genomes. This method was further validated using infectious samples from both animals and humans, including bovine rectal swabs and throat swabs from SARS-CoV-2 patients across various concentration gradients. In both sample types, our hybrid capture-based sequencing method exhibited heightened sensitivity, increased viral genome coverage, and more comprehensive viral identification and characterization. Our method bridges a critical divide between diagnostic detection and genomic surveillance. These findings illustrate that our hybrid capture-based sequencing method can effectively enhance sensitivity to as few as 10 viral copies and genome coverage to >99% in medium-to-high viral loads. This dual capability is particularly impactful for emerging pathogens like SARS-CoV-2, where early detection and genomic characterization are equally vital, thereby addressing the limitations of metagenomics in the surveillance of emerging infectious diseases in complex samples.

Towards Meaningful Interpretation of Molecular Data: Insights Gained from HMMD Challenges in Salmonella Detection for Future NGS Integration in Clinical Microbiology

Background: With advancements in molecular diagnostics, including Highly Multiplexed Microbiological/Medical Countermeasure Diagnostic Devices (HMMDs) and the impending integration of Next-Generation Sequencing (NGS) into clinical microbiology, interpreting the flood of nucleic acid data in a clinically meaningful way has become a crucial challenge. This study focuses on the Luminex xTAG Gastrointestinal Pathogen Panel (GPP) for Salmonella detection, evaluating the impact of MFI threshold adjustments on diagnostic accuracy and exploring the need for an "indeterminate" result category to enhance clinical utility in molecular diagnostics. Methods: A retrospective review of Salmonella-positive cases detected via the Luminex xTAG GPP was conducted from June 2016 to November 2023. Key metrics included patient symptoms, stool culture results, and potential infection sources. Results were analyzed using the assay's MFI cutoffs in Versions 1.11 and 1.12. Statistical comparisons between culture-confirmed and non-confirmed cases were performed using Kruskal-Wallis tests to assess MFI value distributions. Results: Among 2573 tests, 212 were Salmonella-positive under Version 1.11, while 185 were positive under Version 1.12. Adjusting the MFI threshold in Version 1.12 reduced false positives from 40.6% to 38.4% but led to one culture-confirmed positive case being missed. Statistically significant MFI differences were observed between culture-positive and culture-negative cases, suggesting that fixed binary cutoffs may not always yield clinically accurate interpretations. Discussion: The MFI threshold adjustment decreased false positives without fundamentally improving diagnostic accuracy, highlighting the limitations of binary interpretations in HMMDs. Introducing an "indeterminate" category, especially for cases with low MFI values, could aid clinicians in integrating molecular results with patient context. This approach offers a framework for future NGS integration, where nuanced interpretation will be essential to differentiate clinically significant findings from incidental data. Conclusions: Implementing an "indeterminate" interpretation category for HMMDs could enhance clinical decision-making and refine public health surveillance by focusing on clinically relevant findings. As NGS moves toward clinical application, establishing similar interpretive standards will be essential to manage the complexity and volume of molecular data effectively.

Validation of an Automated, End-to-End Metagenomic Sequencing Assay for Agnostic Detection of Respiratory Viruses

BACKGROUND

Current molecular diagnostics are limited in the number and type of detectable pathogens. Metagenomic next-generation sequencing (mNGS) is an emerging, and increasingly feasible, pathogen-agnostic diagnostic approach. Translational barriers prohibit the widespread adoption of this technology in clinical laboratories. We validate an end-to-end mNGS assay for detection of respiratory viruses. Our assay is optimized to reduce turnaround time, lower cost per sample, increase throughput, and deploy secure and actionable bioinformatic results.

METHODS

We validated our assay using residual nasopharyngeal swab specimens from Vancouver General Hospital (n = 359), which were reverse-transcription polymerase chain reaction positive, or negative for influenza, severe acute respiratory syndrome coronavirus 2, and respiratory syncytial virus. We quantified sample stability, assay precision, the effect of background nucleic acid levels, and analytical limits of detection. Diagnostic performance metrics were estimated.

RESULTS

We report that our mNGS assay is highly precise and semiquantitative, with analytical limits of detection ranging from 103 to 104 copies/mL. Our assay is highly specific (100%) and sensitive (61.9% overall: 86.8%; reverse-transcription polymerase chain reaction cycle threshold < 30). Multiplexing capabilities enable processing of up to 55 specimens simultaneously on an Oxford Nanopore GridION device, with results reported within 12 hours.

CONCLUSIONS

This study report outlines the diagnostic performance and feasibility of mNGS for respiratory viral diagnostics, infection control, and public health surveillance. We addressed translational barriers to widespread mNGS adoption.

The application status of sequencing technology in global respiratory infectious disease diagnosis

Next-generation sequencing (NGS) has revolutionized clinical microbiology, particularly in diagnosing respiratory infectious diseases and conducting epidemiological investigations. This narrative review summarizes conventional methods for routine respiratory infection diagnosis, including culture, smear microscopy, immunological assays, image techniques as well as polymerase chain reaction(PCR). In contrast to conventional methods, there is a new detection technology, sequencing technology, and here we mainly focus on the next-generation sequencing NGS, especially metagenomic NGS(mNGS). NGS offers significant advantages over traditional methods. Firstly, mNGS eliminates assumptions about pathogens, leading to faster and more accurate results, thus reducing diagnostic time. Secondly, it allows unbiased identification of known and novel pathogens, offering broad-spectrum coverage. Thirdly, mNGS not only identifies pathogens but also characterizes microbiomes, analyzes human host responses, and detects resistance genes and virulence factors. It can complement targeted sequencing for bacterial and fungal classification. Unlike traditional methods affected by antibiotics, mNGS is less influenced due to the extended survival of pathogen DNA in plasma, broadening its applicability. However, barriers to full integration into clinical practice persist, primarily due to cost constraints and limitations in sensitivity and turnaround time. Despite these challenges, ongoing advancements aim to improve cost-effectiveness and efficiency, making NGS a cornerstone technology for global respiratory infection diagnosis.

Rapid diagnosis of a fox's death case using nanopore sequencing reveals the infection with an Artic-like rabies virus

•We detected a rabies virus (RABV) in a fox's death case within 6 h upon sample receipt using nanopore direct sequencing. •The virus belongs to AL2 sub-lineage, suggesting a high risk of fox-related AL2 RABV on the northeastern border of China. •Nanopore sequencing showed less sensitivity and accuracy, though it helped us rapidly identify the cause of death.

Comparison of the performance of two targeted metagenomic virus capture probe-based methods using reference control materials and clinical samples

Viral enrichment by probe hybridization has been reported to significantly increase the sensitivity of viral metagenomics. This study compares the analytical performance of two targeted metagenomic virus capture probe-based methods: (i) SeqCap EZ HyperCap by Roche (ViroCap) and (ii) Twist Comprehensive Viral Research Panel workflow, for diagnostic use. Sensitivity, specificity, and limit of detection were analyzed using 25 synthetic viral sequences spiked in increasing proportions of human background DNA, eight clinical samples, and American Type Culture Collection (ATCC) Virome Virus Mix. Sensitivity and specificity were 95% and higher for both methods using the synthetic and reference controls as gold standard. Combining thresholds for viral sequence read counts and genome coverage [respectively 500 reads per million (RPM) and 10% coverage] resulted in optimal prediction of true positive results. Limits of detection were approximately 50-500 copies/mL for both methods as determined by ddPCR. Increasing proportions of spike-in cell-free human background sequences up to 99.999% (50 ng/mL) did not negatively affect viral detection, suggesting effective capture of viral sequences. These data show analytical performances in ranges applicable to clinical samples, for both probe hybridization metagenomic approaches. This study supports further steps toward more widespread use of viral metagenomics for pathogen detection, in clinical and surveillance settings using low biomass samples.

IMPORTANCE

Viral metagenomics has been gradually applied for broad-spectrum pathogen detection of infectious diseases, surveillance of emerging diseases, and pathogen discovery. Viral enrichment by probe hybridization methods has been reported to significantly increase the sensitivity of viral metagenomics. During the past years, a specific hybridization panel distributed by Roche has been adopted in a broad range of different clinical and zoonotic settings. Recently, Twist Bioscience has released a new hybridization panel targeting human and animal viruses. This is the first report comparing the performance of viral metagenomic hybridization panels.

Ongoing Cooperative Engagement Facilitates Agile Pandemic and Outbreak Response: Lessons Learned Through Cooperative Engagement Between Uganda and the United States

Pathogens threaten human lives and disrupt economies around the world. This has been clearly illustrated by the current COVID-19 pandemic and outbreaks in livestock and food crops. To manage pathogen emergence and spread, cooperative engagement programs develop and strengthen biosafety, biosecurity, and biosurveillance capabilities among local researchers to detect pathogens. In this case study, we describe the efforts of a collaboration between the Los Alamos National Laboratory and the Uganda Virus Research Institute, the primary viral diagnostic laboratory in Uganda, to implement and ensure the sustainability of sequencing for biosurveillance. We describe the process of establishing this capability along with the lessons learned from both sides of the partnership to inform future cooperative engagement efforts in low- and middle-income countries. We found that by strengthening sequencing capabilities at the Uganda Virus Research Institute before the COVID-19 pandemic, the institute was able to successfully sequence SARS-CoV-2 samples and provide data to the scientific community. We highlight the need to strengthen and sustain capabilities through in-country training, collaborative research projects, and trust.

Ten common issues with reference sequence databases and how to mitigate them

Metagenomic sequencing has revolutionized our understanding of microbiology. While metagenomic tools and approaches have been extensively evaluated and benchmarked, far less attention has been given to the reference sequence database used in metagenomic classification. Issues with reference sequence databases are pervasive. Database contamination is the most recognized issue in the literature; however, it remains relatively unmitigated in most analyses. Other common issues with reference sequence databases include taxonomic errors, inappropriate inclusion and exclusion criteria, and sequence content errors. This review covers ten common issues with reference sequence databases and the potential downstream consequences of these issues. Mitigation measures are discussed for each issue, including bioinformatic tools and database curation strategies. Together, these strategies present a path towards more accurate, reproducible and translatable metagenomic sequencing.

Application of next-generation sequencing to identify different pathogens

Early and precise detection and identification of various pathogens are essential for epidemiological monitoring, disease management, and reducing the prevalence of clinical infectious diseases. Traditional pathogen detection techniques, which include mass spectrometry, biochemical tests, molecular testing, and culture-based methods, are limited in application and are time-consuming. Next generation sequencing (NGS) has emerged as an essential technology for identifying pathogens. NGS is a cutting-edge sequencing method with high throughput that can create massive volumes of sequences with a broad application prospects in the field of pathogen identification and diagnosis. In this review, we introduce NGS technology in detail, summarizes the application of NGS in that identification of different pathogens, including bacteria, fungi, and viruses, and analyze the challenges and outlook for using NGS to identify clinical pathogens. Thus, this work provides a theoretical basis for NGS studies and provides evidence to support the application of NGS in distinguishing various clinical pathogens.

Insights into the structure, functional perspective, and pathogenesis of ZIKV: an updated review

Zika virus (ZIKV) poses a serious threat to the entire world. The rapid spread of ZIKV and recent outbreaks since 2007 have caused worldwide concern about the virus. Diagnosis is complicated because of the cross-reactivity of the virus with other viral antibodies. Currently, the virus is diagnosed by molecular techniques such as RT-PCR and IgM-linked enzyme immunoassays (MAC-ELISA). Recently, outbreaks and epidemics have been caused by ZIKV, and severe clinical symptoms and congenital malformations have also been associated with the virus. Although most ZIKV infections present with a subclinical or moderate flu-like course of illness, severe symptoms such as Guillain-Barre syndrome in adults and microcephaly in children of infected mothers have also been reported. Because there is no reliable cure for ZIKV and no vaccine is available, the public health response has focused primarily on preventing infection, particularly in pregnant women. A comprehensive approach is urgently needed to combat this infection and stop its spread and imminent threat. In view of this, this review aims to present the current structural and functional viewpoints, structure, etiology, clinical prognosis, and measures to prevent this transmission based on the literature and current knowledge. Moreover, we provide thorough description of the current understanding about ZIKV interaction with receptors, and a comparative examination of its similarities and differences with other viruses.

Lung abscess by Fusobacterium nucleatum and Streptococcus spp. co-infection by mNGS: A case series

A lung abscess is a necrotizing infection caused by microbiomes that lead to the loss of healthy lung tissue. The routine culture is a waste of time and yields false-negative results, and clinicians could only choose empiric therapy or use broad-spectrum antibiotics, which could significantly contribute to the problem of resistance or aggravate the condition. We report three patients with a routine-culture-negative lung abscess. The presenting symptoms included fever, cough, dyspnea, and chest pain, and a computed tomography scan revealed a lesion in the lungs. The bronchoalveolar lavage fluid and pleural fluid were tested for pathogens using metagenome next-generation sequencing (mNGS), and the results revealed Fusobacterium nucleatum and Streptococcus spp. (S. constellatus, S. intermedius) as the most represented microbial pathogens. Our data demonstrated that mNGS could be a promising alternative diagnostic tool for pathogen detection, and the pathogen lists indicate that it will be important to focus on the Streptococcus genus rather than the dominant Streptococcus spp. in terms of co-infection of pathogen determined by shotgun mNGS.