Viral metagenomic sequencing in a cohort of international travellers returning with febrile illness

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.

Assessing viral metagenomics for the diagnosis of acute undifferentiated fever in returned travellers: a multicenter cohort study

BACKGROUND

Up to 45% of febrile returning travellers remain undiagnosed after a thorough diagnostic work-up, even at referral centres. Although metagenomic next-generation sequencing (mNGS) has emerged as a promising tool, evidence of its usefulness in imported fever is very limited.

METHODS

Travellers returning with fever were prospectively recruited in three referral clinics from November 2017 to November 2019. Unbiased mNGS optimised for virus detection was performed on serum samples of participants with acute undifferentiated febrile illness (AUFI), and results were compared to those obtained by reference diagnostic methods (RDM).

RESULTS

Among 507 returned febrile travellers, 433(85.4%) presented with AUFI. Dengue virus (n = 86) and Plasmodium spp. (n = 83) were the most common causes of fever. 103/433(23.8%) AUFI remained undiagnosed at the end of the follow-up.Metagenomic next-generation sequencing unveiled potentially pathogenic microorganisms in 196/433(38.7%) AUFI. mNGS identifications were more common in patients with a shorter duration of fever (42.3% in ≤5 days vs 28.7% in >5 days, P = 0.005). Potential causes of fever were revealed in 25/103(24.2%) undiagnosed AUFI and 5/23(21.7%) travellers with severe undiagnosed AUFI. Missed severe aetiologies included eight bacterial identifications and one co-infection of B19 parvovirus and Aspergillus spp.Additional identifications indicating possible co-infections occurred in 29/316(9.2%) travellers with AUFI, and in 11/128(8.6%) travellers with severe AUFI, who had received a diagnosis through RDM. The most common co-infections detected in severe AUFI were caused by Gram-negative bacteria. Serum mNGS was unable to detect >50% of infectious diagnoses achieved by RDM and also yielded 607 non-pathogenic identifications.

DISCUSSION

mNGS of serum can be a valuable diagnostic tool for selected travellers with undiagnosed AUFI or severe disease in addition to reference diagnostic techniques, especially during the first days of symptoms. Nevertheless, mNGS results interpretation presents a great challenge. Further studies evaluating the performance of mNGS using different sample types and protocols tailored to non-viral agents are needed.

Clinical performance of metagenomic next-generation sequencing for diagnosis of pulmonary Aspergillus infection and colonization

Background

Investigations assessing the value of metagenomic next-generation sequencing (mNGS) for distinguish Aspergillus infection from colonization are currently insufficient.

Methods

The performance of mNGS in distinguishing Aspergillus infection from colonization, along with the differences in patients' characteristics, antibiotic adjustment, and lung microbiota, were analyzed.

Results

The abundance of Aspergillus significantly differed between patients with Aspergillus infection (n=36) and colonization (n=32) (P < 0.0001). Receiver operating characteristic (ROC) curve result for bronchoalveolar lavage fluid (BALF) mNGS indicated an area under the curve of 0.894 (95%CI: 0.811-0.976), with an optimal threshold value of 23 for discriminating between Aspergillus infection and colonization. The infection group exhibited a higher proportion of antibiotic adjustments in comparison to the colonization group (50% vs. 12.5%, P = 0.001), with antibiotic escalation being more dominant. Age, length of hospital stay, hemoglobin, cough and chest distress were significantly positively correlated with Aspergillus infection. The abundance of A. fumigatus and Epstein-Barr virus (EBV) significantly increased in the infection group, whereas the colonization group exhibited higher abundance of A. niger.

Conclusion

BALF mNGS is a valuable tool for differentiating between colonization and infection of Aspergillus. Variations in patients' age, length of hospital stay, hemoglobin, cough and chest distress are observable between patients with Aspergillus infection and colonization.

Metagenomics characterization of respiratory viral RNA pathogens in children under five years with severe acute respiratory infection in the Free State, South Africa

Prompt detection of viral respiratory pathogens is crucial in managing respiratory infection including severe acute respiratory infection (SARI). Metagenomics next-generation sequencing (mNGS) and bioinformatics analyses remain reliable strategies for diagnostic and surveillance purposes. This study evaluated the diagnostic utility of mNGS using multiple analysis tools compared with multiplex real-time PCR for the detection of viral respiratory pathogens in children under 5 years with SARI. Nasopharyngeal swabs collected in viral transport media from 84 children admitted with SARI as per the World Health Organization definition between December 2020 and August 2021 in the Free State Province, South Africa, were used in this study. The obtained specimens were subjected to mNGS using the Illumina MiSeq system, and bioinformatics analysis was performed using three web-based analysis tools; Genome Detective, One Codex and Twist Respiratory Viral Research Panel. With average reads of 211323, mNGS detected viral pathogens in 82 (97.6%) of the 84 patients. Viral aetiologies were established in nine previously undetected/missed cases with an additional bacterial aetiology (Neisseria meningitidis) detected in one patient. Furthermore, mNGS enabled the much needed viral genotypic and subtype differentiation and provided significant information on bacterial co-infection despite enrichment for RNA viruses. Sequences of nonhuman viruses, bacteriophages, and endogenous retrovirus K113 (constituting the respiratory virome) were also uncovered. Notably, mNGS had lower detectability rate for severe acute respiratory syndrome coronavirus 2 (missing 18/32 cases). This study suggests that mNGS, combined with multiple/improved bioinformatics tools, is practically feasible for increased viral and bacterial pathogen detection in SARI, especially in cases where no aetiological agent could be identified by available traditional methods.

Clinical Diagnosis Application of Metagenomic Next-Generation Sequencing of Plasma in Suspected Sepsis

Purpose

We analyzed the clinical concordance of mNGS test results from blood samples and improved the clinical efficiency of mNGS in the diagnosis of suspected sepsis pathogens.

Patients and Methods

In this study, 99 samples of suspected blood flow infection were included for plasma mNGS, and the correlation between mNGS results and blood culture results, serum inflammatory indices, clinical symptoms and antibiotic treatment was analyzed, as well as the comparison with the detection rate of BALF pathogens, as well as the classification of different pathogens in the mNGS results were analyzed.

Results

The mNGS pathogen detection rate was higher than that of traditional blood culture (83.02% vs 35.82%). The rate of the mNGS results being consistent with the clinical diagnosis was also higher than that of traditional blood culture (58.49% vs 20.75%). This study shows that bacteria and fungi are the main pathogens in sepsis, and viral sepsis is very rare. In this study, 32% of sepsis patients were secondary to pneumonia. Compared with the pathogen detection rate using alveolar lavage fluid, the detection rate from plasma mNGS was 62.5%. Samples were also easy to sample, noninvasive, and more convenient for clinical application.

Conclusion

This study shows that compared with blood culture, the detection rate of mNGS pathogen that meets the diagnosis of sepsis is higher. We need a combination of multiple indicators to monitor the early diagnosis and treatment of sepsis.

Evolution and emergence of mosquito-borne viruses of medical importance: towards a routine metagenomic surveillance approach

During the last two decades, the world has witnessed the emergence and re-emergence of arthropod-borne viruses, better known as arboviruses. The close contact between sylvatic, rural and peri-urban vector species and humans has been mainly determined by the environment-modifying human activity. The resulting interactions have led to multiple dead-end host infections and have allowed sylvatic arboviruses to eventually adapt to new vectors and hosts, contributing to the establishment of urban transmission cycles of some viruses with enormous epidemiologic impact. The metagenomic next-generation sequencing (NGS) approach has allowed obtaining unbiased sequence information of millions of DNA and RNA molecules from clinical and environmental samples. Robust bioinformatics tools have enabled the assembly of individual sequence reads into contigs and scaffolds partially or completely representing the genomes of the microorganisms and viruses being present in biological samples of clinical relevance. In this review, we describe the different ecological scenarios for the emergence of viral diseases, the virus adaptation process required for the establishment of a new transmission cycle and the usefulness of NGS and computational methods for the discovery and routine genomic surveillance of mosquito-borne viruses in their ecosystems.

Use of Quantitative Metagenomics Next-Generation Sequencing to Confirm Fever of Unknown Origin and Infectious Disease

A body temperature >38.3°C that lasts ≥3 weeks and lacks a clear diagnosis after 1 week of standard hospital examination and treatment is called "fever of unknown origin" (FUO). The main causes of FUO are infections, hematological diseases, autoimmune diseases, and other non-infectious inflammatory diseases. In recent years, quantitative metagenomics next-generation sequencing (Q-mNGS) has been used widely to detect pathogenic microorganisms, especially in the contribution of rare or new (e.g., severe acute respiratory syndrome-coronavirus-2) pathogens. This review addresses the undetermined cause of fever and its evaluation by Q-mNGS.

Performance of Five Metagenomic Classifiers for Virus Pathogen Detection Using Respiratory Samples from a Clinical Cohort

Viral metagenomics is increasingly applied in clinical diagnostic settings for detection of pathogenic viruses. While several benchmarking studies have been published on the use of metagenomic classifiers for abundance and diversity profiling of bacterial populations, studies on the comparative performance of the classifiers for virus pathogen detection are scarce. In this study, metagenomic data sets (n = 88) from a clinical cohort of patients with respiratory complaints were used for comparison of the performance of five taxonomic classifiers: Centrifuge, Clark, Kaiju, Kraken2, and Genome Detective. A total of 1144 positive and negative PCR results for a total of 13 respiratory viruses were used as gold standard. Sensitivity and specificity of these classifiers ranged from 83 to 100% and 90 to 99%, respectively, and was dependent on the classification level and data pre-processing. Exclusion of human reads generally resulted in increased specificity. Normalization of read counts for genome length resulted in a minor effect on overall performance, however it negatively affected the detection of targets with read counts around detection level. Correlation of sequence read counts with PCR Ct-values varied per classifier, data pre-processing (R² range 15.1–63.4%), and per virus, with outliers up to 3 log₁₀ reads magnitude beyond the predicted read count for viruses with high sequence diversity. In this benchmarking study, sensitivity and specificity were within the ranges of use for diagnostic practice when the cut-off for defining a positive result was considered per classifier.

Longitudinal Monitoring of DNA Viral Loads in Transplant Patients Using Quantitative Metagenomic Next-Generation Sequencing

Introduction: Immunocompromised patients are prone to reactivations and (re-)infections of multiple DNA viruses. Viral load monitoring by single-target quantitative PCRs (qPCR) is the current cornerstone for virus quantification. In this study, a metagenomic next-generation sequencing (mNGS) approach was used for the identification and load monitoring of transplantation-related DNA viruses. Methods: Longitudinal plasma samples from six patients that were qPCR-positive for cytomegalovirus (CMV), Epstein-Barr virus (EBV), BK polyomavirus (BKV), adenovirus (ADV), parvovirus B19 (B19V), and torque teno-virus (TTV) were sequenced using the quantitative metagenomic Galileo Viral Panel Solution (Arc Bio, LLC, Cambridge, MA, USA) reagents and bioinformatics pipeline combination. Qualitative and quantitative performance was analysed with a focus on viral load ranges relevant for clinical decision making. Results: All pathogens identified by qPCR were also identified by mNGS. BKV, CMV, and HHV6B were additionally detected by mNGS, and could be confirmed by qPCR or auxiliary bioinformatic analysis. Viral loads determined by mNGS correlated with the qPCR results, with inter-method differences in viral load per virus ranging from 0.19 log₁₀ IU/mL for EBV to 0.90 log₁₀ copies/mL for ADV. TTV, analysed by mNGS in a semi-quantitative way, demonstrated a mean difference of 3.0 log₁₀ copies/mL. Trends over time in viral load determined by mNGS and qPCR were comparable, and clinical thresholds for initiation of treatment were equally identified by mNGS. Conclusions: The Galileo Viral Panel for quantitative mNGS performed comparably to qPCR concerning detection and viral load determination, within clinically relevant ranges of patient management algorithms.