Advanced Virus Detection Technologies Interest Group (AVDTIG): Efforts on High Throughput Sequencing (HTS) for Virus Detection

A comprehensive study comparing virus detection between high throughput sequencing (HTS) and standard protocols in 30 berry selections (12 Fragaria, 10 Vaccinium and 8 Rubus) with known virus profiles was completed. The study examined temporal detection of viruses at four sampling times encompassing two growing seasons. Within the standard protocols, RT-PCR proved better than biological indexing. Detection of known viruses by HTS and RT-PCR nearly mirrored each other. HTS provided superior detection compared to RT-PCR on a wide spectrum of virus variants and discovery of novel viruses. More importantly, in most cases where the two protocols showed parallel virus detection, 11 viruses in 16 berry selections were not consistently detected by both methods at all sampling points. Based on these data we propose a four sampling times/two-year testing requirement for berry and potentially other crops to ensure that no virus remains undetected independent of titer, distribution or other virus/virus or virus/host interactions.

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Current Perspectives on High-Throughput Sequencing (HTS) for Adventitious Virus Detection: Upstream Sample Processing and Library Preparation

Viruses ◽

10.3390/v10100566 ◽

2018 ◽

Vol 10 (10) ◽

pp. 566 ◽

Cited By ~ 9

Author(s):

Siemon Ng ◽

Cassandra Braxton ◽

Marc Eloit ◽

Szi Feng ◽

Romain Fragnoud ◽

...

Keyword(s):

Sample Preparation ◽

Nucleic Acids ◽

High Throughput ◽

High Throughput Sequencing ◽

Virus Detection ◽

Extraction Methods ◽

Control Measures ◽

Acid Extraction ◽

Library Preparation ◽

Sample Processing

A key step for broad viral detection using high-throughput sequencing (HTS) is optimizing the sample preparation strategy for extracting viral-specific nucleic acids since viral genomes are diverse: They can be single-stranded or double-stranded RNA or DNA, and can vary from a few thousand bases to over millions of bases, which might introduce biases during nucleic acid extraction. In addition, viral particles can be enveloped or non-enveloped with variable resistance to pre-treatment, which may influence their susceptibility to extraction procedures. Since the identity of the potential adventitious agents is unknown prior to their detection, efficient sample preparation should be unbiased toward all different viral types in order to maximize the probability of detecting any potential adventitious viruses using HTS. Furthermore, the quality assessment of each step for sample processing is also a critical but challenging aspect. This paper presents our current perspectives for optimizing upstream sample processing and library preparation as part of the discussion in the Advanced Virus Detection Technologies Interest group (AVDTIG). The topics include: Use of nuclease treatment to enrich for encapsidated nucleic acids, techniques for amplifying low amounts of virus nucleic acids, selection of different extraction methods, relevant controls, the use of spike recovery experiments, and quality control measures during library preparation.

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High Throughput Sequencing For Plant Virus Detection and Discovery

Phytopathology ◽

10.1094/phyto-07-18-0257-rvw ◽

2019 ◽

Vol 109 (5) ◽

pp. 716-725 ◽

Cited By ~ 44

Author(s):

D. E. V. Villamor ◽

T. Ho ◽

M. Al Rwahnih ◽

R. R. Martin ◽

I. E. Tzanetakis

Keyword(s):

High Throughput ◽

Plant Virus ◽

High Throughput Sequencing ◽

Virus Detection ◽

Agricultural Crops ◽

Virus Discovery ◽

Plant Virus Detection ◽

Virus Biology ◽

Disease Causality

Over the last decade, virologists have discovered an unprecedented number of viruses using high throughput sequencing (HTS), which led to the advancement of our knowledge on the diversity of viruses in nature, particularly unraveling the virome of many agricultural crops. However, these new virus discoveries have often widened the gaps in our understanding of virus biology; the forefront of which is the actual role of a new virus in disease, if any. Yet, when used critically in etiological studies, HTS is a powerful tool to establish disease causality between the virus and its host. Conversely, with globalization, movement of plant material is increasingly more common and often a point of dispute between countries. HTS could potentially resolve these issues given its capacity to detect and discover. Although many pipelines are available for plant virus discovery, all share a common backbone. A description of the process of plant virus detection and discovery from HTS data are presented, providing a summary of the different pipelines available for scientists’ utility in their research.

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Virus detection in high-throughput sequencing data without a reference genome of the host

Infection Genetics and Evolution ◽

10.1016/j.meegid.2018.09.026 ◽

2018 ◽

Vol 66 ◽

pp. 180-187 ◽

Cited By ~ 3

Author(s):

Jochen Kruppa ◽

Wendy K. Jo ◽

Erhard van der Vries ◽

Martin Ludlow ◽

Albert Osterhaus ◽

...

Keyword(s):

High Throughput ◽

High Throughput Sequencing ◽

Reference Genome ◽

Virus Detection ◽

Sequencing Data ◽

High Throughput Sequencing Data

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Virus Detection by High-Throughput Sequencing of Small RNAs: Large-Scale Performance Testing of Sequence Analysis Strategies

Phytopathology ◽

10.1094/phyto-02-18-0067-r ◽

2019 ◽

Vol 109 (3) ◽

pp. 488-497 ◽

Cited By ~ 29

Author(s):

Sebastien Massart ◽

Michela Chiumenti ◽

Kris De Jonghe ◽

Rachel Glover ◽

Annelies Haegeman ◽

...

Keyword(s):

High Throughput ◽

Large Scale ◽

High Throughput Sequencing ◽

Performance Test ◽

Virus Detection ◽

Performance Testing ◽

Plant Viruses ◽

Reference Sequence ◽

Bioinformatics Pipeline ◽

Double Blind

Recent developments in high-throughput sequencing (HTS), also called next-generation sequencing (NGS), technologies and bioinformatics have drastically changed research on viral pathogens and spurred growing interest in the field of virus diagnostics. However, the reliability of HTS-based virus detection protocols must be evaluated before adopting them for diagnostics. Many different bioinformatics algorithms aimed at detecting viruses in HTS data have been reported but little attention has been paid thus far to their sensitivity and reliability for diagnostic purposes. Therefore, we compared the ability of 21 plant virology laboratories, each employing a different bioinformatics pipeline, to detect 12 plant viruses through a double-blind large-scale performance test using 10 datasets of 21- to 24-nucleotide small RNA (sRNA) sequences from three different infected plants. The sensitivity of virus detection ranged between 35 and 100% among participants, with a marked negative effect when sequence depth decreased. The false-positive detection rate was very low and mainly related to the identification of host genome-integrated viral sequences or misinterpretation of the results. Reproducibility was high (91.6%). This work revealed the key influence of bioinformatics strategies for the sensitive detection of viruses in HTS sRNA datasets and, more specifically (i) the difficulty in detecting viral agents when they are novel or their sRNA abundance is low, (ii) the influence of key parameters at both assembly and annotation steps, (iii) the importance of completeness of reference sequence databases, and (iv) the significant level of scientific expertise needed when interpreting pipeline results. Overall, this work underlines key parameters and proposes recommendations for reliable sRNA-based detection of known and unknown viruses.

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Broad-Range Virus Detection and Discovery Using Microfluidic PCR Coupled with High-throughput Sequencing

10.1101/2020.06.10.145052 ◽

2020 ◽

Author(s):

Ying Tao ◽

Clinton R. Paden ◽

Krista Queen ◽

Jing Zhang ◽

Eishita Tyagi ◽

...

Keyword(s):

High Throughput ◽

High Throughput Sequencing ◽

Virus Detection ◽

Viral Pathogens ◽

Large Numbers ◽

Straightforward Method ◽

Sequence Identification ◽

Pcr Assays ◽

Taxonomic Groups ◽

Next Generation Sequencing Ngs

AbstractThere is a need for a comprehensive and sensitive method to test for a broad range of viral pathogens in samples without any identifiable pathogen detected. Real-time PCR assays are sensitive and rapid, but their specificity limits their utility in detecting divergent agents. Shotgun high-throughput sequencing methods provide unbiased sequence identification, however, they have limited sensitivity and require complex analyses. In order to meet the need for a sensitive, high-throughput virus detection and discovery platform with good sensitivity, we combine two existing technologies, broadly-reactive consensus-degenerate pan-viral group PCR and the MiSeq sequencer (Illumina), using the Access Array (Fluidigm), a commercially-available microfluidic PCR system. Pan-viral group primers target conserved regions of virus taxonomic groups and can amplify known and potentially novel species. The Access Array employs dozens of these assays in parallel, which are then sequenced all at once on the MiSeq. In this study, we run a respiratory panel of pan-viral group PCR assays using AA-PCR-Seq. We validate the panel on a collection of representative human and animal samples, comparing it to qPCR and shotgun next-generation sequencing (NGS). AA-PCR-Seq provides a robust, straightforward method for screening large numbers of samples for virus detection and discovery.

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Use of High-Throughput Sequencing and Two RNA Input Methods to Identify Viruses Infecting Tomato Crops

Microorganisms ◽

10.3390/microorganisms9051043 ◽

2021 ◽

Vol 9 (5) ◽

pp. 1043

Author(s):

Ayoub Maachi ◽

Covadonga Torre ◽

Raquel N. Sempere ◽

Yolanda Hernando ◽

Miguel A. Aranda ◽

...

Keyword(s):

High Throughput ◽

High Throughput Sequencing ◽

Tomato Fruit ◽

Virus Detection ◽

Read Depth ◽

Cdna Libraries ◽

Virus Species ◽

Total Rna ◽

Viral Genomes ◽

First Time

We used high-throughput sequencing to identify viruses on tomato samples showing virus-like symptoms. Samples were collected from crops in the Iberian Peninsula. Either total RNA or double-stranded RNA (dsRNA) were used as starting material to build the cDNA libraries. In total, seven virus species were identified, with pepino mosaic virus being the most abundant one. The dsRNA input provided better coverage and read depth but missed one virus species compared with the total RNA input. By performing in silico analyses, we determined a minimum sequencing depth per sample of 0.2 and 1.5 million reads for dsRNA and rRNA-depleted total RNA inputs, respectively, to detect even the less abundant viruses. Primers and TaqMan probes targeting conserved regions in the viral genomes were designed and/or used for virus detection; all viruses were detected by qRT-PCR/RT-PCR in individual samples, with all except one sample showing mixed infections. Three virus species (Olive latent virus 1, Lettuce ring necrosis virus and Tomato fruit blotch virus) are herein reported for the first time in tomato crops in Spain.

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A Reference Viral Database (RVDB) To Enhance Bioinformatics Analysis of High-Throughput Sequencing for Novel Virus Detection

mSphere ◽

10.1128/mspheredirect.00069-18 ◽

2018 ◽

Vol 3 (2) ◽

Cited By ~ 70

Author(s):

Norman Goodacre ◽

Aisha Aljanahi ◽

Subhiksha Nandakumar ◽

Mike Mikailov ◽

Arifa S. Khan

Keyword(s):

High Throughput ◽

Selection Criteria ◽

High Throughput Sequencing ◽

Bioinformatics Analysis ◽

Virus Detection ◽

Sequence Diversity ◽

Endogenous Retroviruses ◽

Viral Sequence ◽

Novel Virus ◽

Viral Sequences

ABSTRACTDetection of distantly related viruses by high-throughput sequencing (HTS) is bioinformatically challenging because of the lack of a public database containing all viral sequences, without abundant nonviral sequences, which can extend runtime and obscure viral hits. Our reference viral database (RVDB) includes all viral, virus-related, and virus-like nucleotide sequences (excluding bacterial viruses), regardless of length, and with overall reduced cellular sequences. Semantic selection criteria (SEM-I) were used to select viral sequences from GenBank, resulting in a first-generation viral database (VDB). This database was manually and computationally reviewed, resulting in refined, semantic selection criteria (SEM-R), which were applied to a new download of updated GenBank sequences to create a second-generation VDB. Viral entries in the latter were clustered at 98% by CD-HIT-EST to reduce redundancy while retaining high viral sequence diversity. The viral identity of the clustered representative sequences (creps) was confirmed by BLAST searches in NCBI databases and HMMER searches in PFAM and DFAM databases. The resulting RVDB contained a broad representation of viral families, sequence diversity, and a reduced cellular content; it includes full-length and partial sequences and endogenous nonretroviral elements, endogenous retroviruses, and retrotransposons. Testing of RVDBv10.2, with an in-house HTS transcriptomic data set indicated a significantly faster run for virus detection than interrogating the entirety of the NCBI nonredundant nucleotide database, which contains all viral sequences but also nonviral sequences. RVDB is publically available for facilitating HTS analysis, particularly for novel virus detection. It is meant to be updated on a regular basis to include new viral sequences added to GenBank.IMPORTANCETo facilitate bioinformatics analysis of high-throughput sequencing (HTS) data for the detection of both known and novel viruses, we have developed a new reference viral database (RVDB) that provides a broad representation of different virus species from eukaryotes by including all viral, virus-like, and virus-related sequences (excluding bacteriophages), regardless of their size. In particular, RVDB contains endogenous nonretroviral elements, endogenous retroviruses, and retrotransposons. Sequences were clustered to reduce redundancy while retaining high viral sequence diversity. A particularly useful feature of RVDB is the reduction of cellular sequences, which can enhance the run efficiency of large transcriptomic and genomic data analysis and increase the specificity of virus detection.

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A Multicenter Study To Evaluate the Performance of High-Throughput Sequencing for Virus Detection

mSphere ◽

10.1128/msphere.00307-17 ◽

2017 ◽

Vol 2 (5) ◽

Cited By ~ 10

Author(s):

Arifa S. Khan ◽

Siemon H. S. Ng ◽

Olivier Vandeputte ◽

Aisha Aljanahi ◽

Avisek Deyati ◽

...

Keyword(s):

Sample Preparation ◽

Cell Line ◽

High Throughput ◽

Future Development ◽

High Throughput Sequencing ◽

Collaborative Study ◽

Virus Detection ◽

Biological Products ◽

Reference Virus ◽

Complex Technology

ABSTRACT Recent high-throughput sequencing (HTS) investigations have resulted in unexpected discoveries of known and novel viruses in a variety of sample types, including research materials, clinical materials, and biological products. Therefore, HTS can be a powerful tool for supplementing current methods for demonstrating the absence of adventitious or unwanted viruses in biological products, particularly when using a new cell line. However, HTS is a complex technology with different platforms, which needs standardization for evaluation of biologics. This collaborative study was undertaken to investigate detection of different virus types using two different HTS platforms. The results of the independently performed studies demonstrated a similar sensitivity of virus detection, regardless of the different sample preparation and processing procedures and bioinformatic analyses done in the three laboratories. Comparable HTS detection of different virus types supports future development of reference virus materials for standardization and validation of different HTS platforms. The capability of high-throughput sequencing (HTS) for detection of known and unknown viruses makes it a powerful tool for broad microbial investigations, such as evaluation of novel cell substrates that may be used for the development of new biological products. However, like any new assay, regulatory applications of HTS need method standardization. Therefore, our three laboratories initiated a study to evaluate performance of HTS for potential detection of viral adventitious agents by spiking model viruses in different cellular matrices to mimic putative materials for manufacturing of biologics. Four model viruses were selected based upon different physical and biochemical properties and commercial availability: human respiratory syncytial virus (RSV), Epstein-Barr virus (EBV), feline leukemia virus (FeLV), and human reovirus (REO). Additionally, porcine circovirus (PCV) was tested by one laboratory. Independent samples were prepared for HTS by spiking intact viruses or extracted viral nucleic acids, singly or mixed, into different HeLa cell matrices (resuspended whole cells, cell lysate, or total cellular RNA). Data were obtained using different sequencing platforms (Roche 454, Illumina HiSeq1500 or HiSeq2500). Bioinformatic analyses were performed independently by each laboratory using available tools, pipelines, and databases. The results showed that comparable virus detection was obtained in the three laboratories regardless of sample processing, library preparation, sequencing platform, and bioinformatic analysis: between 0.1 and 3 viral genome copies per cell were detected for all of the model viruses used. This study highlights the potential for using HTS for sensitive detection of adventitious viruses in complex biological samples containing cellular background. IMPORTANCE Recent high-throughput sequencing (HTS) investigations have resulted in unexpected discoveries of known and novel viruses in a variety of sample types, including research materials, clinical materials, and biological products. Therefore, HTS can be a powerful tool for supplementing current methods for demonstrating the absence of adventitious or unwanted viruses in biological products, particularly when using a new cell line. However, HTS is a complex technology with different platforms, which needs standardization for evaluation of biologics. This collaborative study was undertaken to investigate detection of different virus types using two different HTS platforms. The results of the independently performed studies demonstrated a similar sensitivity of virus detection, regardless of the different sample preparation and processing procedures and bioinformatic analyses done in the three laboratories. Comparable HTS detection of different virus types supports future development of reference virus materials for standardization and validation of different HTS platforms.

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A Versatile Processing Workflow to Enable Pathogen Detection in Clinical Samples from Organs Using VIDISCA

Diagnostics ◽

10.3390/diagnostics11050791 ◽

2021 ◽

Vol 11 (5) ◽

pp. 791

Author(s):

Alba Folgueiras-González ◽

Robin van den Braak ◽

Martin Deijs ◽

Lia van der Hoek ◽

Ad de Groof

Keyword(s):

High Throughput ◽

Pathogen Detection ◽

High Throughput Sequencing ◽

Genetic Material ◽

Virus Detection ◽

Detection Sensitivity ◽

Clinical Samples ◽

Tissue Samples ◽

Sequencing Technologies ◽

Organic Extraction

In recent years, refined molecular methods coupled with powerful high throughput sequencing technologies have increased the potential of virus discovery in clinical samples. However, host genetic material remains a complicating factor that interferes with discovery of novel viruses in solid tissue samples as the relative abundance of the virus material is low. Physical enrichment processing methods, although usually complicated, labor-intensive, and costly, have proven to be successful for improving sensitivity of virus detection in complex samples. In order to further increase detectability, we studied the application of fast and simple high-throughput virus enrichment methods on tissue homogenates. Probe sonication in high EDTA concentrations, organic extraction with Vertrel™ XF, or a combination of both, were applied prior to chromatography-like enrichment using Capto™ Core 700 resin, after which effects on virus detection sensitivity by the VIDISCA method were determined. Sonication in the presence of high concentrations of EDTA showed the best performance with an increased proportion of viral reads, up to 9.4 times, yet minimal effect on the host background signal. When this sonication procedure in high EDTA concentrations was followed by organic extraction with Vertrel™ XF and two rounds of core bead chromatography enrichment, an increase up to 10.5 times in the proportion of viral reads in the processed samples was achieved, with reduction of host background sequencing. We present a simple and semi-high-throughput method that can be used to enrich homogenized tissue samples for viral reads.

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