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Lopez-Labrador FX, Huber M, Sidorov IA, Brown JR, Cuypers L, Laenen L, Vanmechelen B, Maes P, Fischer N, Pichler I, Storey N, Atkinson L, Schmutz S, Kufner V, van Boheemen S, Mulders CE, Grundhoff A, Blümke P, Robitaille A, Cinek O, Hubáčková K, Mourik K, Boers SA, Stauber L, Salmona M, Cappy P, Ramette A, Franze' A, LeGoff J, Claas ECJ, Rodriguez C, de Vries JJC. Multicenter benchmarking of short and long read wet lab protocols for clinical viral metagenomics. J Clin Virol 2024; 173:105695. [PMID: 38823290 DOI: 10.1016/j.jcv.2024.105695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2024] [Revised: 04/10/2024] [Accepted: 05/18/2024] [Indexed: 06/03/2024]
Abstract
Metagenomics is gradually being implemented for diagnosing infectious diseases. However, in-depth protocol comparisons for viral detection have been limited to individual sets of experimental workflows and laboratories. In this study, we present a benchmark of metagenomics protocols used in clinical diagnostic laboratories initiated by the European Society for Clinical Virology (ESCV) Network on NGS (ENNGS). A mock viral reference panel was designed to mimic low biomass clinical specimens. The panel was used to assess the performance of twelve metagenomic wet lab protocols currently in use in the diagnostic laboratories of participating ENNGS member institutions. Both Illumina and Nanopore, shotgun and targeted capture probe protocols were included. Performance metrics sensitivity, specificity, and quantitative potential were assessed using a central bioinformatics pipeline. Overall, viral pathogens with loads down to 104 copies/ml (corresponding to CT values of 31 in our PCR assays) were detected by all the evaluated metagenomic wet lab protocols. In contrast, lower abundant mixed viruses of CT values of 35 and higher were detected only by a minority of the protocols. Considering the reference panel as the gold standard, optimal thresholds to define a positive result were determined per protocol, based on the horizontal genome coverage. Implementing these thresholds, sensitivity and specificity of the protocols ranged from 67 to 100 % and 87 to 100 %, respectively. A variety of metagenomic protocols are currently in use in clinical diagnostic laboratories. Detection of low abundant viral pathogens and mixed infections remains a challenge, implying the need for standardization of metagenomic analysis for use in clinical settings.
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Affiliation(s)
- F Xavier Lopez-Labrador
- Virology Laboratory, Genomics and Health Area, Center for Public Health Research (FISABIO-Public Health), Generalitat Valenciana, Valencia, Spain; Microbiology & Ecology Department, Medical School, University of Valencia, Spain; and CIBERESP, Instituto de Salud Carlos III, Spain
| | - Michael Huber
- Institute of Medical Virology, University of Zurich, Switzerland
| | - Igor A Sidorov
- Clinical Microbiological Laboratory, Department of Medical Microbiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Julianne R Brown
- Microbiology, Virology and Infection Prevention & Control, Great Ormond Street Hospital for Children NHS Foundation Trust, London, United Kingdom
| | - Lize Cuypers
- Department of Laboratory Medicine, University Hospitals Leuven, and Laboratory of Clinical Microbiology, KU, Leuven, Belgium
| | - Lies Laenen
- Department of Laboratory Medicine, University Hospitals Leuven, and Laboratory of Clinical Microbiology, KU, Leuven, Belgium
| | - Bert Vanmechelen
- Laboratory of Clinical and Epidemiological Virology, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, KU Leuven, Belgium
| | - Piet Maes
- Laboratory of Clinical and Epidemiological Virology, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, KU Leuven, Belgium
| | - Nicole Fischer
- University Medical Center Hamburg-Eppendorf, UKE Institute for Medical Microbiology, Virology and Hygiene, Germany
| | - Ian Pichler
- Institute of Medical Virology, University of Zurich, Switzerland
| | - Nathaniel Storey
- Microbiology, Virology and Infection Prevention & Control, Great Ormond Street Hospital for Children NHS Foundation Trust, London, United Kingdom
| | - Laura Atkinson
- Microbiology, Virology and Infection Prevention & Control, Great Ormond Street Hospital for Children NHS Foundation Trust, London, United Kingdom
| | - Stefan Schmutz
- Institute of Medical Virology, University of Zurich, Switzerland
| | - Verena Kufner
- Institute of Medical Virology, University of Zurich, Switzerland
| | | | | | | | | | | | - Ondrej Cinek
- Department of Medical Microbiology, 2nd Faculty of Medicine, Charles University, and University Hospital Motol, Prague, Czech Republic
| | - Klára Hubáčková
- Department of Medical Microbiology, 2nd Faculty of Medicine, Charles University, and University Hospital Motol, Prague, Czech Republic
| | - Kees Mourik
- Clinical Microbiological Laboratory, Department of Medical Microbiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Stefan A Boers
- Clinical Microbiological Laboratory, Department of Medical Microbiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Lea Stauber
- Institute for Infectious Diseases, University of Bern, Switzerland
| | - Maud Salmona
- Virology Department, AP-HP, Hôpital Saint Louis, F-75010 Paris, France
| | | | - Alban Ramette
- Institute for Infectious Diseases, University of Bern, Switzerland
| | - Alessandra Franze'
- Virology Laboratory, Genomics and Health Area, Center for Public Health Research (FISABIO-Public Health), Generalitat Valenciana, Valencia, Spain
| | - Jerome LeGoff
- Virology Department, AP-HP, Hôpital Saint Louis, F-75010 Paris, France
| | - Eric C J Claas
- Clinical Microbiological Laboratory, Department of Medical Microbiology, Leiden University Medical Center, Leiden, the Netherlands
| | | | - Jutte J C de Vries
- Clinical Microbiological Laboratory, Department of Medical Microbiology, Leiden University Medical Center, Leiden, the Netherlands.
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Mourik K, Sidorov I, Carbo EC, van der Meer D, Boot A, Kroes ACM, Claas ECJ, Boers SA, de Vries JJC. Comparison of the performance of two targeted metagenomic virus capture probe-based methods using reference control materials and clinical samples. J Clin Microbiol 2024; 62:e0034524. [PMID: 38757981 PMCID: PMC11237577 DOI: 10.1128/jcm.00345-24] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Accepted: 04/05/2024] [Indexed: 05/18/2024] Open
Abstract
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.
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Affiliation(s)
- Kees Mourik
- Department of Medical Microbiology, Leiden University Center for Infectious Diseases, Leiden University Medical Center, Leiden, the Netherlands
| | - Igor Sidorov
- Department of Medical Microbiology, Leiden University Center for Infectious Diseases, Leiden University Medical Center, Leiden, the Netherlands
| | - Ellen C. Carbo
- Department of Medical Microbiology, Leiden University Center for Infectious Diseases, Leiden University Medical Center, Leiden, the Netherlands
| | | | | | - Aloysius C. M. Kroes
- Department of Medical Microbiology, Leiden University Center for Infectious Diseases, Leiden University Medical Center, Leiden, the Netherlands
| | - Eric C. J. Claas
- Department of Medical Microbiology, Leiden University Center for Infectious Diseases, Leiden University Medical Center, Leiden, the Netherlands
| | - Stefan A. Boers
- Department of Medical Microbiology, Leiden University Center for Infectious Diseases, Leiden University Medical Center, Leiden, the Netherlands
| | - Jutte J. C. de Vries
- Department of Medical Microbiology, Leiden University Center for Infectious Diseases, Leiden University Medical Center, Leiden, the Netherlands
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Wani AK, Chopra C, Dhanjal DS, Akhtar N, Singh H, Bhau P, Singh A, Sharma V, Pinheiro RSB, Américo-Pinheiro JHP, Singh R. Metagenomics in the fight against zoonotic viral infections: A focus on SARS-CoV-2 analogues. J Virol Methods 2024; 323:114837. [PMID: 37914040 DOI: 10.1016/j.jviromet.2023.114837] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 10/24/2023] [Accepted: 10/27/2023] [Indexed: 11/03/2023]
Abstract
Zoonotic viral infections continue to pose significant threats to global public health, as highlighted by the COVID-19 pandemic caused by the SARS-CoV-2 virus. The emergence of SARS-CoV-2 served as a stark reminder of the potential for zoonotic transmission of viruses from animals to humans. Understanding the origins and dynamics of zoonotic viruses is critical for early detection, prevention, and effective management of future outbreaks. Metagenomics has emerged as a powerful tool for investigating the virome of diverse ecosystems, shedding light on the diversity of viral populations, their hosts, and potential zoonotic spillover events. We provide an in-depth examination of metagenomic approaches, including, NGS metagenomics, shotgun metagenomics, viral metagenomics, and single-virus metagenomics, highlighting their strengths and limitations in identifying and characterizing zoonotic viral pathogens. This review underscores the pivotal role of metagenomics in enhancing our ability to detect, monitor, and mitigate zoonotic viral infections, using SARS-CoV-2 analogues as a case study. We emphasize the need for continued interdisciplinary collaboration among virologists, ecologists, and bioinformaticians to harness the full potential of metagenomic approaches in safeguarding public health against emerging zoonotic threats.
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Affiliation(s)
- Atif Khurshid Wani
- School of Bioengineering and Biosciences, Lovely Professional University, Punjab 144411, India
| | - Chirag Chopra
- School of Bioengineering and Biosciences, Lovely Professional University, Punjab 144411, India
| | - Daljeet Singh Dhanjal
- School of Bioengineering and Biosciences, Lovely Professional University, Punjab 144411, India
| | - Nahid Akhtar
- School of Bioengineering and Biosciences, Lovely Professional University, Punjab 144411, India
| | - Himanshu Singh
- School of Bioengineering and Biosciences, Lovely Professional University, Punjab 144411, India
| | - Poorvi Bhau
- School of Biotechnology, Shri Mata Vaishno Devi University, Katra, Jammu and Kashmir, India
| | - Anjuvan Singh
- School of Bioengineering and Biosciences, Lovely Professional University, Punjab 144411, India
| | - Varun Sharma
- NMC Genetics India Pvt. Ltd, Gurugram, Harayana, India
| | - Rafael Silvio Bonilha Pinheiro
- School of Veterinary Medicine and Animal Science, Department of Animal Production, São Paulo State University (UNESP), Botucatu, SP, Brazil
| | - Juliana Heloisa Pinê Américo-Pinheiro
- Department of Forest Science, Soils and Environment, School of Agronomic Sciences, São Paulo State University (UNESP), Ave. Universitária, 3780, Botucatu, SP 18610-034, Brazil; Graduate Program in Environmental Sciences, Brazil University, Street Carolina Fonseca, 584, São Paulo, SP 08230-030, Brazil
| | - Reena Singh
- School of Bioengineering and Biosciences, Lovely Professional University, Punjab 144411, India.
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Ogunbayo AE, Mogotsi MT, Sondlane H, Sabiu S, Nyaga MM. Metagenomics characterization of respiratory viral RNA pathogens in children under five years with severe acute respiratory infection in the Free State, South Africa. J Med Virol 2023; 95:e28753. [PMID: 37212321 PMCID: PMC10952945 DOI: 10.1002/jmv.28753] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 03/14/2023] [Accepted: 04/03/2023] [Indexed: 05/23/2023]
Abstract
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.
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Affiliation(s)
- Ayodeji E. Ogunbayo
- Next Generation Sequencing Unit and Division of VirologyFaculty of Health Sciences, University of the Free StateBloemfonteinSouth Africa
| | - Milton T. Mogotsi
- Next Generation Sequencing Unit and Division of VirologyFaculty of Health Sciences, University of the Free StateBloemfonteinSouth Africa
| | - Hlengiwe Sondlane
- Next Generation Sequencing Unit and Division of VirologyFaculty of Health Sciences, University of the Free StateBloemfonteinSouth Africa
| | - Saheed Sabiu
- Department of Biotechnology and Food ScienceDurban University of TechnologyDurbanSouth Africa
| | - Martin M. Nyaga
- Next Generation Sequencing Unit and Division of VirologyFaculty of Health Sciences, University of the Free StateBloemfonteinSouth Africa
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Waite DW, Liefting L, Delmiglio C, Chernyavtseva A, Ha HJ, Thompson JR. Development and Validation of a Bioinformatic Workflow for the Rapid Detection of Viruses in Biosecurity. Viruses 2022; 14:v14102163. [PMID: 36298719 PMCID: PMC9610911 DOI: 10.3390/v14102163] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Accepted: 09/25/2022] [Indexed: 11/05/2022] Open
Abstract
The field of biosecurity has greatly benefited from the widespread adoption of high-throughput sequencing technologies, for its ability to deeply query plant and animal samples for pathogens for which no tests exist. However, the bioinformatics analysis tools designed for rapid analysis of these sequencing datasets are not developed with this application in mind, limiting the ability of diagnosticians to standardise their workflows using published tool kits. We sought to assess previously published bioinformatic tools for their ability to identify plant- and animal-infecting viruses while distinguishing from the host genetic material. We discovered that many of the current generation of virus-detection pipelines are not adequate for this task, being outperformed by more generic classification tools. We created synthetic MinION and HiSeq libraries simulating plant and animal infections of economically important viruses and assessed a series of tools for their suitability for rapid and accurate detection of infection, and further tested the top performing tools against the VIROMOCK Challenge dataset to ensure that our findings were reproducible when compared with international standards. Our work demonstrated that several methods provide sensitive and specific detection of agriculturally important viruses in a timely manner and provides a key piece of ground truthing for method development in this space.
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Affiliation(s)
- David W. Waite
- Plant Health and Environment Laboratory, Ministry for Primary Industries, P.O. Box 2095, Auckland 1140, New Zealand
- Correspondence:
| | - Lia Liefting
- Plant Health and Environment Laboratory, Ministry for Primary Industries, P.O. Box 2095, Auckland 1140, New Zealand
| | - Catia Delmiglio
- Plant Health and Environment Laboratory, Ministry for Primary Industries, P.O. Box 2095, Auckland 1140, New Zealand
| | | | - Hye Jeong Ha
- Animal Health Laboratory, Ministry for Primary Industries, Upper Hutt 5018, New Zealand
| | - Jeremy R. Thompson
- Plant Health and Environment Laboratory, Ministry for Primary Industries, P.O. Box 2095, Auckland 1140, New Zealand
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