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Viral Diagnostics Using Next-Generation Sequencing
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Viral Diagnostics Using Next-Generation Sequencing

A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Technologies and Resources for Genetics".

Deadline for manuscript submissions: closed (31 July 2019) | Viewed by 37772

Special Issue Editor

Dr. Alban Ramette

E-Mail Website
Guest Editor
Institute for Infectious Diseases (IFIK), University of Bern, Bern, Switzerland
Interests: microbiology; epidemiology; biostatistics; microbial ecology; bioinformatics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Diagnostic virology is undergoing a revolution due to technological developments, especially in the area of Next-Generation Sequencing (NGS). The rapid production of large amounts of sequence data combined with in-depth bioinformatic analyses enable new insights into the identity, abundance, genome organization, and molecular epidemiology of viral agents in clinical samples. We are calling for articles for a Special Issue on “Viral Diagnostics Using Next-Generation Sequencing” that will consist of either original research articles and short-communications on the detection, identification, enrichment, genomic characterization, resistance profiling, and bioinformatic applications related to the diagnostic of viruses; or examine the current state of the field through review articles. We also welcome comparative methodological approaches of wet or dry laboratory aspects of viral diagnostics using NGS, demonstrating the superiority of specific approaches in terms of turnover time, costs, ease of implementation, and biological information generated for applications in the clinical routine setting. We will accept manuscripts starting from February 2019 until the submission deadline.

Dr. Alban Ramette
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Genes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • virus
  • Next-Generation Sequencing
  • diagnostics
  • clinical
  • bioinformatics
  • nucleic acid
  • high throughput
  • computing

Published Papers (6 papers)

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Research

18 pages, 3614 KiB  
Article
NCBI’s Virus Discovery Hackathon: Engaging Research Communities to Identify Cloud Infrastructure Requirements
by Ryan Connor, Rodney Brister, Jan P. Buchmann, Ward Deboutte, Rob Edwards, Joan Martí-Carreras, Mike Tisza, Vadim Zalunin, Juan Andrade-Martínez, Adrian Cantu, Michael D’Amour, Alexandre Efremov, Lydia Fleischmann, Laura Forero-Junco, Sanzhima Garmaeva, Melissa Giluso, Cody Glickman, Margaret Henderson, Benjamin Kellman, David Kristensen, Carl Leubsdorf, Kyle Levi, Shane Levi, Suman Pakala, Vikas Peddu, Alise Ponsero, Eldred Ribeiro, Farrah Roy, Lindsay Rutter, Surya Saha, Migun Shakya, Ryan Shean, Matthew Miller, Benjamin Tully, Christopher Turkington, Ken Youens-Clark, Bert Vanmechelen and Ben Busbyadd Show full author list remove Hide full author list
Genes 2019, 10(9), 714; https://0-doi-org.brum.beds.ac.uk/10.3390/genes10090714 - 16 Sep 2019
Cited by 9 | Viewed by 7626
Abstract
A wealth of viral data sits untapped in publicly available metagenomic data sets when it might be extracted to create a usable index for the virological research community. We hypothesized that work of this complexity and scale could be done in a hackathon [...] Read more.
A wealth of viral data sits untapped in publicly available metagenomic data sets when it might be extracted to create a usable index for the virological research community. We hypothesized that work of this complexity and scale could be done in a hackathon setting. Ten teams comprised of over 40 participants from six countries, assembled to create a crowd-sourced set of analysis and processing pipelines for a complex biological data set in a three-day event on the San Diego State University campus starting 9 January 2019. Prior to the hackathon, 141,676 metagenomic data sets from the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) were pre-assembled into contiguous assemblies (contigs) by NCBI staff. During the hackathon, a subset consisting of 2953 SRA data sets (approximately 55 million contigs) was selected, which were further filtered for a minimal length of 1 kb. This resulted in 4.2 million (Mio) contigs, which were aligned using BLAST against all known virus genomes, phylogenetically clustered and assigned metadata. Out of the 4.2 Mio contigs, 360,000 contigs were labeled with domains and an additional subset containing 4400 contigs was screened for virus or virus-like genes. The work yielded valuable insights into both SRA data and the cloud infrastructure required to support such efforts, revealing analysis bottlenecks and possible workarounds thereof. Mainly: (i) Conservative assemblies of SRA data improves initial analysis steps; (ii) existing bioinformatic software with weak multithreading/multicore support can be elevated by wrapper scripts to use all cores within a computing node; (iii) redesigning existing bioinformatic algorithms for a cloud infrastructure to facilitate its use for a wider audience; and (iv) a cloud infrastructure allows a diverse group of researchers to collaborate effectively. The scientific findings will be extended during a follow-up event. Here, we present the applied workflows, initial results, and lessons learned from the hackathon. Full article
(This article belongs to the Special Issue Viral Diagnostics Using Next-Generation Sequencing)
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15 pages, 2149 KiB  
Article
Two Years of Viral Metagenomics in a Tertiary Diagnostics Unit: Evaluation of the First 105 Cases
by Verena Kufner, Andreas Plate, Stefan Schmutz, Dominique L. Braun, Huldrych F. Günthard, Riccarda Capaul, Andrea Zbinden, Nicolas J. Mueller, Alexandra Trkola and Michael Huber
Genes 2019, 10(9), 661; https://0-doi-org.brum.beds.ac.uk/10.3390/genes10090661 - 29 Aug 2019
Cited by 37 | Viewed by 5563
Abstract
Metagenomic next-generation sequencing (mNGS) can capture the full spectrum of viral pathogens in a specimen and has the potential to become an all-in-one solution for virus diagnostics. To date, clinical application is still in an early phase and limitations remain. Here, we evaluated [...] Read more.
Metagenomic next-generation sequencing (mNGS) can capture the full spectrum of viral pathogens in a specimen and has the potential to become an all-in-one solution for virus diagnostics. To date, clinical application is still in an early phase and limitations remain. Here, we evaluated the impact of viral mNGS for cases analyzed over two years in a tertiary diagnostics unit. High throughput mNGS was performed upon request by the treating clinician in cases where the etiology of infection remained unknown or the initial differential diagnosis was very broad. The results were compared to conventional routine testing regarding outcome and workload. In total, 163 specimens from 105 patients were sequenced. The main sample types were cerebrospinal fluid (34%), blood (33%) and throat swabs (10%). In the majority of the cases, viral encephalitis/meningitis or respiratory infection was suspected. In parallel, conventional virus diagnostic tests were performed (mean 18.5 individually probed targets/patients). mNGS detected viruses in 34 cases (32%). While often confirmatory, in multiple cases, the identified viruses were not included in the selected routine diagnostic tests. Two years of mNGS in a tertiary diagnostics unit demonstrated the advantages of a single, untargeted approach for comprehensive, rapid and efficient virus diagnostics, confirming the utility of mNGS in complementing current routine tests. Full article
(This article belongs to the Special Issue Viral Diagnostics Using Next-Generation Sequencing)
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12 pages, 2052 KiB  
Article
Rapid and Cost-Efficient Enterovirus Genotyping from Clinical Samples Using Flongle Flow Cells
by Carole Grädel, Miguel Angel Terrazos Miani, Maria Teresa Barbani, Stephen L Leib, Franziska Suter-Riniker and Alban Ramette
Genes 2019, 10(9), 659; https://0-doi-org.brum.beds.ac.uk/10.3390/genes10090659 - 29 Aug 2019
Cited by 27 | Viewed by 9437
Abstract
Enteroviruses affect millions of people worldwide and are of significant clinical importance. The standard method for enterovirus identification and genotyping still relies on Sanger sequencing of short diagnostic amplicons. In this study, we assessed the feasibility of nanopore sequencing using the new flow [...] Read more.
Enteroviruses affect millions of people worldwide and are of significant clinical importance. The standard method for enterovirus identification and genotyping still relies on Sanger sequencing of short diagnostic amplicons. In this study, we assessed the feasibility of nanopore sequencing using the new flow cell “Flongle” for fast, cost-effective, and accurate genotyping of human enteroviruses from clinical samples. PCR amplification of partial VP1 gene was performed from multiple patient samples, which were multiplexed together after barcoding PCR and sequenced multiple times on Flongle flow cells. The nanopore consensus sequences obtained from mapping reads to a reference database were compared to their Sanger sequence counterparts. Using clinical specimens sampled over different years, we were able to correctly identify enterovirus species and genotypes for all tested samples, even when doubling the number of barcoded samples on one flow cell. Average sequence identity across sequencing runs was >99.7%. Phylogenetic analysis showed that the consensus sequences achieved with Flongle delivered accurate genotyping. We conclude that the new Flongle-based assay with its fast turnover time, low cost investment, and low cost per sample represents an accurate, reproducible, and cost-effective platform for enterovirus identification and genotyping. Full article
(This article belongs to the Special Issue Viral Diagnostics Using Next-Generation Sequencing)
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19 pages, 1117 KiB  
Article
Viral Metagenomics in the Clinical Realm: Lessons Learned from a Swiss-Wide Ring Trial
by Thomas Junier, Michael Huber, Stefan Schmutz, Verena Kufner, Osvaldo Zagordi, Stefan Neuenschwander, Alban Ramette, Jakub Kubacki, Claudia Bachofen, Weihong Qi, Florian Laubscher, Samuel Cordey, Laurent Kaiser, Christian Beuret, Valérie Barbié, Jacques Fellay and Aitana Lebrand
Genes 2019, 10(9), 655; https://0-doi-org.brum.beds.ac.uk/10.3390/genes10090655 - 28 Aug 2019
Cited by 25 | Viewed by 4823
Abstract
Shotgun metagenomics using next generation sequencing (NGS) is a promising technique to analyze both DNA and RNA microbial material from patient samples. Mostly used in a research setting, it is now increasingly being used in the clinical realm as well, notably to support [...] Read more.
Shotgun metagenomics using next generation sequencing (NGS) is a promising technique to analyze both DNA and RNA microbial material from patient samples. Mostly used in a research setting, it is now increasingly being used in the clinical realm as well, notably to support diagnosis of viral infections, thereby calling for quality control and the implementation of ring trials (RT) to benchmark pipelines and ensure comparable results. The Swiss NGS clinical virology community therefore decided to conduct a RT in 2018, in order to benchmark current metagenomic workflows used at Swiss clinical virology laboratories, and thereby contribute to the definition of common best practices. The RT consisted of two parts (increments), in order to disentangle the variability arising from the experimental compared to the bioinformatics parts of the laboratory pipeline. In addition, the RT was also designed to assess the impact of databases compared to bioinformatics algorithms on the final results, by asking participants to perform the bioinformatics analysis with a common database, in addition to using their own in-house database. Five laboratories participated in the RT (seven pipelines were tested). We observed that the algorithms had a stronger impact on the overall performance than the choice of the reference database. Our results also suggest that differences in sample preparation can lead to significant differences in the performance, and that laboratories should aim for at least 5–10 Mio reads per sample and use depth of coverage in addition to other interpretation metrics such as the percent of coverage. Performance was generally lower when increasing the number of viruses per sample. The lessons learned from this pilot study will be useful for the development of larger-scale RTs to serve as regular quality control tests for laboratories performing NGS analyses of viruses in a clinical setting. Full article
(This article belongs to the Special Issue Viral Diagnostics Using Next-Generation Sequencing)
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12 pages, 1841 KiB  
Article
Viral Sequences Detection by High-Throughput Sequencing in Cerebrospinal Fluid of Individuals with and without Central Nervous System Disease
by Manuel Schibler, Francisco Brito, Marie-Céline Zanella, Evgeny M. Zdobnov, Florian Laubscher, Arnaud G L’Huillier, Juan Ambrosioni, Noémie Wagner, Klara M Posfay-Barbe, Mylène Docquier, Eduardo Schiffer, Georges L. Savoldelli, Roxane Fournier, Lauriane Lenggenhager, Samuel Cordey and Laurent Kaiser
Genes 2019, 10(8), 625; https://0-doi-org.brum.beds.ac.uk/10.3390/genes10080625 - 19 Aug 2019
Cited by 12 | Viewed by 4111
Abstract
Meningitis, encephalitis, and myelitis are various forms of acute central nervous system (CNS) inflammation, which can coexist and lead to serious sequelae. Known aetiologies include infections and immune-mediated processes. Despite advances in clinical microbiology over the past decades, the cause of acute CNS [...] Read more.
Meningitis, encephalitis, and myelitis are various forms of acute central nervous system (CNS) inflammation, which can coexist and lead to serious sequelae. Known aetiologies include infections and immune-mediated processes. Despite advances in clinical microbiology over the past decades, the cause of acute CNS inflammation remains unknown in approximately 50% of cases. High-throughput sequencing was performed to search for viral sequences in cerebrospinal fluid (CSF) samples collected from 26 patients considered to have acute CNS inflammation of unknown origin, and 10 patients with defined causes of CNS diseases. In order to better grasp the clinical significance of viral sequence data obtained in CSF, 30 patients without CNS disease who had a lumbar puncture performed during elective spinal anaesthesia were also analysed. One case of human astrovirus (HAstV)-MLB2-related meningitis and disseminated infection was identified. No other viral sequences that can easily be linked to CNS inflammation were detected. Viral sequences obtained in all patient groups are discussed. While some of them reflect harmless viral infections, others result from reagent or sample contamination, as well as index hopping. Altogether, this study highlights the potential of high-throughput sequencing in identifying previously unknown viral neuropathogens, as well as the interpretation issues related to its application in clinical microbiology. Full article
(This article belongs to the Special Issue Viral Diagnostics Using Next-Generation Sequencing)
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12 pages, 1342 KiB  
Article
Viral Metagenomics on Cerebrospinal Fluid
by Arthur W. D. Edridge, Martin Deijs, Ingeborg E. van Zeggeren, Cormac M. Kinsella, Maarten F. Jebbink, Margreet Bakker, Diederik van de Beek, Matthijs C. Brouwer and Lia van der Hoek
Genes 2019, 10(5), 332; https://0-doi-org.brum.beds.ac.uk/10.3390/genes10050332 - 30 Apr 2019
Cited by 36 | Viewed by 5477
Abstract
Identifying the causative pathogen in central nervous system (CNS) infections is crucial for patient management and prognosis. Many viruses can cause CNS infections, yet screening for each individually is costly and time-consuming. Most metagenomic assays can theoretically detect all pathogens, but often fail [...] Read more.
Identifying the causative pathogen in central nervous system (CNS) infections is crucial for patient management and prognosis. Many viruses can cause CNS infections, yet screening for each individually is costly and time-consuming. Most metagenomic assays can theoretically detect all pathogens, but often fail to detect viruses because of their small genome and low viral load. Viral metagenomics overcomes this by enrichment of the viral genomic content in a sample. VIDISCA-NGS is one of the available workflows for viral metagenomics, which requires only a small input volume and allows multiplexing of multiple samples per run. The performance of VIDISCA-NGS was tested on 45 cerebrospinal fluid (CSF) samples from patients with suspected CNS infections in which a virus was identified and quantified by polymerase chain reaction. Eighteen were positive for an RNA virus, and 34 for a herpesvirus. VIDISCA-NGS detected all RNA viruses with a viral load >2 × 104 RNA copies/mL (n = 6) and 8 of 12 of the remaining low load samples. Only one herpesvirus was identified by VIDISCA-NGS, however, when withholding a DNase treatment, 11 of 18 samples with a herpesvirus load >104 DNA copies/mL were detected. Our results indicate that VIDISCA-NGS has the capacity to detect low load RNA viruses in CSF. Herpesvirus DNA in clinical samples is probably non-encapsidated and therefore difficult to detect by VIDISCA-NGS. Full article
(This article belongs to the Special Issue Viral Diagnostics Using Next-Generation Sequencing)
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