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van Boheemen S, van Rijn AL, Pappas N, Carbo EC, Vorderman RHP, Sidorov I, van T Hof PJ, Mei H, Claas ECJ, Kroes ACM, de Vries JJC. Retrospective Validation of a Metagenomic Sequencing Protocol for Combined Detection of RNA and DNA Viruses Using Respiratory Samples from Pediatric Patients. J Mol Diagn 2020; 22:196-207. [PMID: 31837435 PMCID: PMC7106021 DOI: 10.1016/j.jmoldx.2019.10.007] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2019] [Revised: 09/16/2019] [Accepted: 10/07/2019] [Indexed: 02/07/2023] Open
Abstract
Viruses are the main cause of respiratory tract infections. Metagenomic next-generation sequencing (mNGS) enables unbiased detection of all potential pathogens. To apply mNGS in viral diagnostics, sensitive and simultaneous detection of RNA and DNA viruses is needed. Herein, were studied the performance of an in-house mNGS protocol for routine diagnostics of viral respiratory infections with potential for automated pan-pathogen detection. The sequencing protocol and bioinformatics analysis were designed and optimized, including exogenous internal controls. Subsequently, the protocol was retrospectively validated using 25 clinical respiratory samples. The developed protocol using Illumina NextSeq 500 sequencing showed high repeatability. Use of the National Center for Biotechnology Information's RefSeq database as opposed to the National Center for Biotechnology Information's nucleotide database led to enhanced specificity of classification of viral pathogens. A correlation was established between read counts and PCR cycle threshold value. Sensitivity of mNGS, compared with PCR, varied up to 83%, with specificity of 94%, dependent on the cutoff for defining positive mNGS results. Viral pathogens only detected by mNGS, not present in the routine diagnostic workflow, were influenza C, KI polyomavirus, cytomegalovirus, and enterovirus. Sensitivity and analytical specificity of this mNGS protocol were comparable to PCR and higher when considering off-PCR target viral pathogens. One single test detected all potential viral pathogens and simultaneously obtained detailed information on detected viruses.
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Affiliation(s)
- Sander van Boheemen
- Department of Medical Microbiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | - Anneloes L van Rijn
- Department of Medical Microbiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands.
| | - Nikos Pappas
- Sequencing Analysis Support Core, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | - Ellen C Carbo
- Department of Medical Microbiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | - Ruben H P Vorderman
- Sequencing Analysis Support Core, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | - Igor Sidorov
- Department of Medical Microbiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | - Peter J van T Hof
- Sequencing Analysis Support Core, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | - Hailiang Mei
- Sequencing Analysis Support Core, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | - Eric C J Claas
- Department of Medical Microbiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | - Aloys C M Kroes
- Department of Medical Microbiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | - Jutte J C de Vries
- Department of Medical Microbiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
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Glanz VY, Myasoedova VA, Grechko AV, Orekhov AN. Inhibition of sialidase activity as a therapeutic approach. DRUG DESIGN DEVELOPMENT AND THERAPY 2018; 12:3431-3437. [PMID: 30349196 PMCID: PMC6186905 DOI: 10.2147/dddt.s176220] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
The demand for novel anti-influenza drugs persists, which is highlighted by the recent pandemics of influenza affecting thousands of people across the globe. One of the approaches to block the virus spreading is inhibiting viral sialidase (neuraminidase). This enzyme cleaves the sialic acid link between the newly formed virions and the host cell surface liberating the virions from the cell and maintaining the cycle of infection. Viral neuraminidases appear therefore as attractive therapeutic targets for preventing further spread of influenza infection. Compared to ion channel blockers that were the first approved anti-influenza drugs, neuraminidase inhibitors are well tolerated and target both influenza A and B viruses. Moreover, neuraminidase/sialidase inhibitors may be useful for managing some other human pathologies, such as cancer. In this review, we discuss the available knowledge on neuraminidase or sialidase inhibitors, their design, clinical application, and the current challenges.
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Affiliation(s)
- Victor Yu Glanz
- Department of Genetics, Cytology and Bioengineering, Faculty of Biology and Medicine, Voronezh State University, Voronezh, Russia
| | - Veronika A Myasoedova
- Laboratory of Angiopathology, Institute of General Pathology and Pathophysiology, Moscow, Russia,
| | - Andrey V Grechko
- Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology, Moscow, Russia
| | - Alexander N Orekhov
- Laboratory of Angiopathology, Institute of General Pathology and Pathophysiology, Moscow, Russia, .,Institute for Atherosclerosis Research, Skolkovo Innovative Center, Moscow, Russia,
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