Prolonged detection of complete viral genomes demonstrated by SARS-CoV-2 sequencing of serial respiratory specimens.
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ABSTRACT:
SUBMITTER: Zuckerman NS
PROVIDER: S-EPMC8341697 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:In late 2019, a novel coronavirus began spreading in Wuhan, China, causing a potentially lethal respiratory viral infection. By early 2020, the novel coronavirus, called SARS-CoV-2, had spread globally, causing the COVID-19 pandemic. The infection and mutation rates of SARS-CoV-2 make it amenable to tracking introduction, spread and evolution by viral genome sequencing. Efforts to develop effective public health policies, therapeutics, or vaccines to treat or prevent COVID-19 are also expected to benefit from tracking mutations of the SARS-CoV-2 virus. Here we describe a set of comprehensive working protocols, from viral RNA extraction to analysis using established visualization tools, for high throughput sequencing of SARS-CoV-2 viral genomes using a MinION instrument. This set of protocols should serve as a reliable "how-to" reference for generating quality SARS-CoV-2 genome sequences with ARTIC primer sets and long-read nanopore sequencing technology. In addition, many of the preparation, quality control, and analysis steps will be generally applicable to other sequencing platforms.
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Project description:Gene annotation in viruses often relies upon similarity search methods. These methods possess high specificity but some genes may be missed, either those unique to a particular genome or those highly divergent from known homologs. To identify potentially missing viral genes we have analyzed all complete viral genomes currently available in GenBank with a specialized and augmented version of the gene finding program GeneMarkS. In particular, by implementing genome-specific self-training protocols we have better adjusted the GeneMarkS statistical models to sequences of viral genomes. Hundreds of new genes were identified, some in well studied viral genomes. For example, a new gene predicted in the genome of the Epstein-Barr virus was shown to encode a protein similar to alpha-herpesvirus minor tegument protein UL14 with heat shock functions. Convincing evidence of this similarity was obtained after only 12 PSI-BLAST iterations. In another example, several iterations of PSI-BLAST were required to demonstrate that a gene predicted in the genome of Alcelaphine herpesvirus 1 encodes a BALF1-like protein which is thought to be involved in apoptosis regulation and, potentially, carcinogenesis. New predictions were used to refine annotations of viral genomes in the RefSeq collection curated by the National Center for Biotechnology Information. Importantly, even in those cases where no sequence similarities were detected, GeneMarkS significantly reduced the number of primary targets for experimental characterization by identifying the most probable candidate genes. The new genome annotations were stored in VIOLIN, an interactive database which provides access to similarity search tools for up-to-date analysis of predicted viral proteins.
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Project description:With the advent of Next Generation Sequencing (NGS) technologies, the ability to generate large amounts of sequence data has revolutionized the genomics field. Most RNA viruses have relatively small genomes in comparison to other organisms and as such, would appear to be an obvious success story for the use of NGS technologies. However, due to the relatively low abundance of viral RNA in relation to host RNA, RNA viruses have proved relatively difficult to sequence using NGS technologies. Here we detail a simple, robust methodology, without the use of ultra-centrifugation, filtration or viral enrichment protocols, to prepare RNA from diagnostic clinical tissue samples, cell monolayers and tissue culture supernatant, for subsequent sequencing on the Roche 454 platform.As representative RNA viruses, full genome sequence was successfully obtained from known lyssaviruses belonging to recognized species and a novel lyssavirus species using these protocols and assembling the reads using de novo algorithms. Furthermore, genome sequences were generated from considerably less than 200 ng RNA, indicating that manufacturers' minimum template guidance is conservative. In addition to obtaining genome consensus sequence, a high proportion of SNPs (Single Nucleotide Polymorphisms) were identified in the majority of samples analyzed.The approaches reported clearly facilitate successful full genome lyssavirus sequencing and can be universally applied to discovering and obtaining consensus genome sequences of RNA viruses from a variety of sources.
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Project description:Accumulating evidence supports the high prevalence of co-infections among Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) patients, and their potential to worsen the clinical outcome of COVID-19. However, there are few data on Southern Hemisphere populations, and most studies to date have investigated a narrow spectrum of viruses using targeted qRT-PCR. Here we assessed respiratory viral co-infections among SARS-CoV-2 patients in Australia, through respiratory virome characterization. Nasopharyngeal swabs of 92 SARS-CoV-2-positive cases were sequenced using pan-viral hybrid-capture and the Twist Respiratory Virus Panel. In total, 8% of cases were co-infected, with rhinovirus (6%) or influenzavirus (2%). Twist capture also achieved near-complete sequencing (>?90% coverage,?>?tenfold depth) of the SARS-CoV-2 genome in 95% of specimens with Ct?<?30. Our results highlight the importance of assessing all pathogens in symptomatic patients, and the dual-functionality of Twist hybrid-capture, for SARS-CoV-2 whole-genome sequencing without amplicon generation and the simultaneous identification of viral co-infections with ease.
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Project description:BackgroundNosocomially acquired severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) infection has become the most significant pandemic of our lifetime. Though its transmission was essentially attributed to droplets from an infected person, with recent advancements in knowledge, aerosol transmission seems to be a viable pathway, as well. Because of the lower biological load in ambient aerosol, detection of SARS-CoV-2 is challenging. A few recent attempts of sampling large aerosol volumes and using next-generation sequencing (NGS) to detect the presence of SARS-CoV-2 in the air at very low levels gave positive results. These results suggest the potential of using this technique to detect the presence of SARS-CoV-2 and use it as an early warning signal for possible outbreak or recurrence of coronavirus disease 2019 (COVID-19).AimTo assess efficacy of comprehensive respiratory viral panel (CRVP) sequencing and RT-PCR for low-level identification of SARS-CoV-2 and other respiratory viruses in indoor air.MethodsA large volume of indoor aerosol samples from three major hospitals involved in COVID-19 care in Kuwait was collected. Viral RNA was isolated and subjected to comprehensive respiratory viral panel sequencing (CRVP) as per the standard protocol to detect the SARS-CoV-2 and other respiratory viruses in the hospital aerosol and monitor variations within the sequences. RT-PCR was also employed to estimate the viral load of SARS-CoV-2.Findings13 of 15 (86.7%) samples exhibited SARS-CoV-2 with a relative abundance of 0.2-33.3%. The co-occurrence of human adenoviruses (type C1, C2, C5, C4), respiratory syncytial virus (RSV), influenza B, and non-SARS-CoV-229E were also recorded. Alignment of SARS-CoV-2 sequences against the reference strain of Wuhan China revealed variations in the form of single nucleotide polymorphisms (SNPs-17), insertions and deletions (indels-1). These variations were predicted to create missense (16), synonymous (15), frameshift (1) and stop-gained (1) mutations with a high (2), low (15), and moderate (16) impact.ConclusionsOur results suggest that using CRVP on a large volume aerosol sample was a valuable tool for detecting SARS-CoV-2 in indoor aerosols of health care settings. Owing to its higher sensitivity, it can be employed as a surveillance strategy in the post COVID times to act as an early warning system to possibly control future outbreaks.
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Project description:We have assessed two approaches to sequencing complete human cytomegalovirus (HCMV) genomes (236 kbp) in DNA extracted from infected cell cultures (strains 3157, HAN13, HAN20 and HAN38) or clinical specimens (strains JP and 3301). The first approach involved amplifying genomes from the DNA samples as overlapping PCR products, sequencing these by the Sanger method, acquiring reads from a capillary instrument and assembling these using the Staden programs. The second approach involved generating sequence data from the DNA samples by using an Illumina Genome Analyzer (IGA), processing the filtered reads by reference-independent (de novo) assembly, utilizing the resulting sequence to direct reference-dependent assembly of the same data and finishing by limited PCR sequencing. Both approaches were successful. In particular, the investigation demonstrated the utility of IGA data for efficiently sequencing genomes from clinical samples containing as little as 3 % HCMV DNA. Analysis of the genome sequences obtained showed that each of the strains grown in cell culture was a mutant. Certain of the mutations were shared among strains from independent clinical sources, thus suggesting that they may have arisen in a common ancestor during natural infection. Moreover, one of the strains (JP) sequenced directly from a clinical specimen was mutated in two genes, one of which encodes a proposed immune-evasion function, viral interleukin-10. These observations imply that HCMV mutants exist in human infections.
| S-EPMC2885759 | biostudies-literature
Project description:BackgroundWhole genome sequencing of viruses and bacteriophages is often hindered because of the need for large quantities of genomic material. A method is described that combines single plaque sequencing with an optimization of Sequence Independent Single Primer Amplification (SISPA). This method can be used for de novo whole genome next-generation sequencing of any cultivable virus without the need for large-scale production of viral stocks or viral purification using centrifugal techniques.MethodsA single viral plaque of a variant of the 2009 pandemic H1N1 human Influenza A virus was isolated and amplified using the optimized SISPA protocol. The sensitivity of the SISPA protocol presented here was tested with bacteriophage F_HA0480sp/Pa1651 DNA. The amplified products were sequenced with 454 and Illumina HiSeq platforms. Mapping and de novo assemblies were performed to analyze the quality of data produced from this optimized method.ResultsAnalysis of the sequence data demonstrated that from a single viral plaque of Influenza A, a mapping assembly with 3590-fold average coverage representing 100% of the genome could be produced. The de novo assembled data produced contigs with 30-fold average sequence coverage, representing 96.5% of the genome. Using only 10 pg of starting DNA from bacteriophage F_HA0480sp/Pa1651 in the SISPA protocol resulted in sequencing data that gave a mapping assembly with 3488-fold average sequence coverage, representing 99.9% of the reference and a de novo assembly with 45-fold average sequence coverage, representing 98.1% of the genome.ConclusionsThe optimized SISPA protocol presented here produces amplified product that when sequenced will give high quality data that can be used for de novo assembly. The protocol requires only a single viral plaque or as little as 10 pg of DNA template, which will facilitate rapid identification of viruses during an outbreak and viruses that are difficult to propagate.
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Project description:Genomic sequencing is crucial to understanding the epidemiology and evolution of SARS-CoV-2. Often, genomic studies rely on remnant diagnostic material, typically nasopharyngeal swabs, as input into whole genome SARS-CoV-2 next-generation sequencing pipelines. Saliva has proven to be a safe and stable specimen for the detection of SARS-CoV-2 RNA via traditional diagnostic assays, however saliva is not commonly used for SARS-CoV-2 sequencing. Using the ARTIC Network amplicon-generation approach with sequencing on the Oxford Nanopore MinION, we demonstrate that sequencing SARS-CoV-2 from saliva produces genomes comparable to those from nasopharyngeal swabs, and that RNA extraction is necessary to generate complete genomes from saliva. In this study, we show that saliva is a useful specimen type for genomic studies of SARS-CoV-2.
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Project description:Genomic sequencing is crucial to understanding the epidemiology and evolution of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Often, genomic studies rely on remnant diagnostic material, typically nasopharyngeal (NP) swabs, as input into whole-genome SARS-CoV-2 next-generation sequencing pipelines. Saliva has proven to be a safe and stable specimen for the detection of SARS-CoV-2 RNA via traditional diagnostic assays; however, saliva is not commonly used for SARS-CoV-2 sequencing. Using the ARTIC Network amplicon-generation approach with sequencing on the Oxford Nanopore MinION, we demonstrate that sequencing SARS-CoV-2 from saliva produces genomes comparable to those from NP swabs, and that RNA extraction is necessary to generate complete genomes from saliva. In this study, we show that saliva is a useful specimen type for genomic studies of SARS-CoV-2.
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Project description:Segmented RNA viruses are a complex group of RNA viruses with multisegment genomes. Reconstructing complete segmented viruses is crucial for advancing our understanding of viral diversity, evolution, and public health impact. Using metatranscriptomic data to identify known and novel segmented viruses has sped up the survey of segmented viruses in various ecosystems. However, the high genetic diversity and the difficulty in binning complete segmented genomes present significant challenges in segmented virus reconstruction. Current virus detection tools are primarily used to identify nonsegmented viral genomes. This study presents SegVir, a novel tool designed to identify segmented RNA viruses and reconstruct their complete genomes from complex metatranscriptomes. SegVir leverages both close and remote homology searches to accurately detect conserved and divergent viral segments. Additionally, we introduce a new method that can evaluate the genome completeness and conservation based on gene content. Our evaluations on simulated datasets demonstrate SegVir's superior sensitivity and precision compared to existing tools. Moreover, in experiments using real data, we identified some virus segments missing in the NCBI database, underscoring SegVir's potential to enhance viral metagenome analysis. The source code and supporting data of SegVir are available via https://github.com/HubertTang/SegVir.
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