Implementation of next-generation sequencing for virus identification in veterinary diagnostic laboratories.
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ABSTRACT:
SUBMITTER: Kubacki J
PROVIDER: S-EPMC7953084 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Molecular diagnosis of complex dual genome mitochondrial disorders is a challenge. It requires the identification of deleterious mutations in one of the ~1,500 nuclear genes and the mitochondrial genome. If the molecular defect is in the mitochondrial genome, quantification of degree of mutation load (heteroplasmy) in affected tissues is important. Due to the extreme clinical and genetic heterogeneity, conventional sequence analysis of the candidate genes one-by-one is impractical, if not impossible. The newly developed massively parallel next generation sequencing (NGS) technique, that allows simultaneous sequence analysis of multiple target genes, when appropriately validated with deep coverage and proper quality controls, can be used as an effective comprehensive diagnostic approach in CLIA certified clinical laboratories.
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Project description:IntroductionCurrent clinical detection of Human immunodeficiency virus 1 (HIV-1) is used to target viral genes and proteins. However, the immunoassay, such as viral culture or Polymerase Chain Reaction (PCR), lacks accuracy in the diagnosis, as these conventional assays rely on the stable genome and HIV-1 is a highly-mutated virus. Next generation sequencing (NGS) promises to be transformative for the practice of infectious disease, and the rapidly reducing cost and processing time mean that this will become a feasible technology in diagnostic and research laboratories in the near future. The technology offers the superior sensitivity to detect the pathogenic viruses, including unknown and unexpected strains.AimTo leverage the NGS technology in order to improve current HIV-1 diagnosis and genotyping methods.Materials and methodsTen blood samples were collected from HIV-1 infected patients which were diagnosed by RT PCR at Singapore Communicable Disease Centre, Tan Tock Seng Hospital from October 2014 to March 2015. Viral RNAs were extracted from blood plasma and reversed into cDNA. The HIV-1 cDNA samples were cleaned up using a PCR purification kit and the sequencing library was prepared and identified through MiSeq.ResultsTwo common mutations were observed in all ten samples. The common mutations were identified at genome locations 1908 and 2104 as missense and silent mutations respectively, conferring S37N and S3S found on aspartic protease and reverse transcriptase subunits.ConclusionThe common mutations identified in this study were not previously reported, therefore suggesting the potential for them to be used for identification of viral infection, disease transmission and drug resistance. This was especially the case for, missense mutation S37N which could cause an amino acid change in viral proteases thus reducing the binding affinity of some protease inhibitors. Thus, the unique common mutations identified in this study could be used as diagnostic biomarkers to indicate the origin of infection as being from Singapore.
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Project description:We present, on behalf of EuroGentest and the European Society of Human Genetics, guidelines for the evaluation and validation of next-generation sequencing (NGS) applications for the diagnosis of genetic disorders. The work was performed by a group of laboratory geneticists and bioinformaticians, and discussed with clinical geneticists, industry and patients' representatives, and other stakeholders in the field of human genetics. The statements that were written during the elaboration of the guidelines are presented here. The background document and full guidelines are available as supplementary material. They include many examples to assist the laboratories in the implementation of NGS and accreditation of this service. The work and ideas presented by others in guidelines that have emerged elsewhere in the course of the past few years were also considered and are acknowledged in the full text. Interestingly, a few new insights that have not been cited before have emerged during the preparation of the guidelines. The most important new feature is the presentation of a 'rating system' for NGS-based diagnostic tests. The guidelines and statements have been applauded by the genetic diagnostic community, and thus seem to be valuable for the harmonization and quality assurance of NGS diagnostics in Europe.
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Project description:NGPS is a method for de-novo, full-length protein sequencing in high throughput. The method is based on cleavage of the protein at semi-random sites by microwave-assisted acid hydrolysis (MAAH), enrichment of LC-MS/MS amenable peptides from the hydrolysate by solid-phase-extraction, LC-MS/MS analysis, de-novo long peptide tag sequencing of resulting peptides and assembly of peptide tags into consensus contigs.
2017-04-03 | PXD003804 | Pride
Project description:We conducted an unbiased metagenomics survey using plasma from patients with chronic hepatitis B, chronic hepatitis C, autoimmune hepatitis (AIH), non-alcoholic steatohepatitis (NASH), and patients without liver disease (control). RNA and DNA libraries were sequenced from plasma filtrates enriched in viral particles to catalog virus populations. Hepatitis viruses were readily detected at high coverage in patients with chronic viral hepatitis B and C, but only a limited number of sequences resembling other viruses were found. The exception was a library from a patient diagnosed with hepatitis C virus (HCV) infection that contained multiple sequences matching GB virus C (GBV-C). Abundant GBV-C reads were also found in plasma from patients with AIH, whereas Torque teno virus (TTV) was found at high frequency in samples from patients with AIH and NASH. After taxonomic classification of sequences by BLASTn, a substantial fraction in each library, ranging from 35% to 76%, remained unclassified. These unknown sequences were assembled into scaffolds along with virus, phage and endogenous retrovirus sequences and then analyzed by BLASTx against the non-redundant protein database. Nearly the full genome of a heretofore-unknown circovirus was assembled and many scaffolds that encoded proteins with similarity to plant, insect and mammalian viruses. The presence of this novel circovirus was confirmed by PCR. BLASTx also identified many polypeptides resembling nucleo-cytoplasmic large DNA viruses (NCLDV) proteins. We re-evaluated these alignments with a profile hidden Markov method, HHblits, and observed inconsistencies in the target proteins reported by the different algorithms. This suggests that sequence alignments are insufficient to identify NCLDV proteins, especially when these alignments are only to small portions of the target protein. Nevertheless, we have now established a reliable protocol for the identification of viruses in plasma that can also be adapted to other patient samples such as urine, bile, saliva and other body fluids.
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Project description:Avian paramyxoviruses 1 has the ability to edit its P gene to generate three amino-coterminal proteins (P, V and W), but its kinetic change is unclear. In this study, next-generation sequencing (NGS) was used to analyze the P-gene editing of Newcastle disease virus (NDV). Transcriptome analysis of chicken embryonic tissues and bursa of fabricius showed the P-gene editing frequencies were 45.46-52.70%. To investigate the rules of P-gene editing along time, the ratio of PVW was determined by PCR based deep sequencing at multiple time points in cells infected with velogenic and lentogenic strain respectively. The results confirmed similar editing frequencies with transcriptome data and the PVW ratios were stable along time among different NDVs, but had a greater V-gene transcript on velogenic strain infection (P<0.001), which were different from previous reports. Also, it was shown that the number of inserted G residues in P-derived transcripts was not limited to +9G, and +10G transcripts were identified. These results confirmed the NDV P-gene editing frequencies and provided a novel point of view on NDV P-gene editing with NDV virulence.
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Project description:The increasing incidence of West Nile virus (WNV) in the Euro-Mediterranean area warrants the implementation of effective surveillance programs in animals. A crucial step in the fight against the disease is the evaluation of the capacity of the veterinary labs to accurately detect the infection in animal populations. In this context, the animal virology network of the MediLabSecure project organized an external quality assessment (EQA) to evaluate the WNV molecular and serological diagnostic capacities of beneficiary veterinary labs. Laboratories from 17 Mediterranean and Black Sea countries participated. The results of the triplex real time RT-PCR for simultaneous detection and differentiation of WNV lineage 1 (L1), lineage 2 (L2) and Usutu virus (USUV) were highly satisfactory, especially for L1 and L2, with detection rates of 97.9% and 100%, respectively. For USUV, 75% of the labs reported correct results. More limitations were observed for the generic detection of flaviviruses using conventional reverse-transcription polymerase chain reaction (RT-PCR), since only 46.1% reported correct results in the whole panel. As regards the serological panel, the results were excellent for the generic detection of WNV antibodies. More variability was observed for the specific detection of IgM antibodies with a higher percentage of incorrect results mainly in samples with low titers. This EQA provides a good overview of the WNV (and USUV) diagnostic performance of the involved veterinary labs and demonstrates that the implemented training program was successful in upgrading their diagnostic capacities.
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Project description:Virus pandemics have happened, are happening and will happen again. In recent decades, the rate of zoonotic viral spillover into humans has accelerated, mirroring the expansion of our global footprint and travel network, including the expansion of viral vectors and the destruction of natural spaces, bringing humans closer to wild animals. Once viral cross-species transmission to humans occurs, transmission cannot be stopped by cement walls but by developing barriers based on knowledge that can prevent or reduce the effects of any pandemic. Controlling a local transmission affecting few individuals is more efficient that confronting a community outbreak in which infections cannot be traced. Genetic detection, identification, and characterization of infectious agents using next-generation sequencing (NGS) has been proven to be a powerful tool allowing for the development of fast PCR-based molecular assays, the rapid development of vaccines based on mRNA and DNA, the identification of outbreaks, transmission dynamics and spill-over events, the detection of new variants and treatment of vaccine resistance mutations, the development of direct-acting antiviral drugs, the discovery of relevant minority variants to improve knowledge of the viral life cycle, strengths and weaknesses, the potential for becoming dominant to take appropriate preventive measures, and the discovery of new routes of viral transmission.
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Project description:A critical challenge in genetic diagnostics is the computational assessment of candidate splice variants, specifically the interpretation of nucleotide changes located outside of the highly conserved dinucleotide sequences at the 5' and 3' ends of introns. To address this gap, we developed the Super Quick Information-content Random-forest Learning of Splice variants (SQUIRLS) algorithm. SQUIRLS generates a small set of interpretable features for machine learning by calculating the information-content of wild-type and variant sequences of canonical and cryptic splice sites, assessing changes in candidate splicing regulatory sequences, and incorporating characteristics of the sequence such as exon length, disruptions of the AG exclusion zone, and conservation. We curated a comprehensive collection of disease-associated splice-altering variants at positions outside of the highly conserved AG/GT dinucleotides at the termini of introns. SQUIRLS trains two random-forest classifiers for the donor and for the acceptor and combines their outputs by logistic regression to yield a final score. We show that SQUIRLS transcends previous state-of-the-art accuracy in classifying splice variants as assessed by rank analysis in simulated exomes, and is significantly faster than competing methods. SQUIRLS provides tabular output files for incorporation into diagnostic pipelines for exome and genome analysis, as well as visualizations that contextualize predicted effects of variants on splicing to make it easier to interpret splice variants in diagnostic settings.
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Project description:BackgroundThe discovery and mapping of genomic variants is an essential step in most analysis done using sequencing reads. There are a number of mature software packages and associated pipelines that can identify single nucleotide polymorphisms (SNPs) with a high degree of concordance. However, the same cannot be said for tools that are used to identify the other types of variants. Indels represent the second most frequent class of variants in the human genome, after single nucleotide polymorphisms. The reliable detection of indels is still a challenging problem, especially for variants that are longer than a few bases.ResultsWe have developed a set of algorithms and heuristics collectively called indelMINER to identify indels from whole genome resequencing datasets using paired-end reads. indelMINER uses a split-read approach to identify the precise breakpoints for indels of size less than a user specified threshold, and supplements that with a paired-end approach to identify larger variants that are frequently missed with the split-read approach. We use simulated and real datasets to show that an implementation of the algorithm performs favorably when compared to several existing tools.ConclusionsindelMINER can be used effectively to identify indels in whole-genome resequencing projects. The output is provided in the VCF format along with additional information about the variant, including information about its presence or absence in another sample. The source code and documentation for indelMINER can be freely downloaded from www.bx.psu.edu/miller_lab/indelMINER.tar.gz .
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