Assessment of Metagenomic Sequencing and qPCR for Detection of Influenza D Virus in Bovine Respiratory Tract Samples
High throughput sequencing is currently revolutionizing the genomics field and providing new approaches to the detection and characterization of microorganisms. The objective of this study was to assess the detection of influenza D virus (IDV) in bovine respiratory tract samples using two sequencing...
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Published in | Viruses Vol. 12; no. 8; p. 814 |
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Language | English |
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28.07.2020
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Abstract | High throughput sequencing is currently revolutionizing the genomics field and providing new approaches to the detection and characterization of microorganisms. The objective of this study was to assess the detection of influenza D virus (IDV) in bovine respiratory tract samples using two sequencing platforms (MiSeq and Nanopore (GridION)), and species-specific qPCR. An IDV-specific qPCR was performed on 232 samples (116 nasal swabs and 116 tracheal washes) that had been previously subject to virome sequencing using MiSeq. Nanopore sequencing was performed on 19 samples positive for IDV by either MiSeq or qPCR. Nanopore sequence data was analyzed by two bioinformatics methods: What’s In My Pot (WIMP, on the EPI2ME platform), and an in-house developed analysis pipeline. The agreement of IDV detection between qPCR and MiSeq was 82.3%, between qPCR and Nanopore was 57.9% (in-house) and 84.2% (WIMP), and between MiSeq and Nanopore was 89.5% (in-house) and 73.7% (WIMP). IDV was detected by MiSeq in 14 of 17 IDV qPCR-positive samples with Cq (cycle quantification) values below 31, despite multiplexing 50 samples for sequencing. When qPCR was regarded as the gold standard, the sensitivity and specificity of MiSeq sequence detection were 28.3% and 98.9%, respectively. We conclude that both MiSeq and Nanopore sequencing are capable of detecting IDV in clinical specimens with a range of Cq values. Sensitivity may be further improved by optimizing sequence data analysis, improving virus enrichment, or reducing the degree of multiplexing. |
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AbstractList | High throughput sequencing is currently revolutionizing the genomics field and providing new approaches to the detection and characterization of microorganisms. The objective of this study was to assess the detection of influenza D virus (IDV) in bovine respiratory tract samples using two sequencing platforms (MiSeq and Nanopore (GridION)), and species-specific qPCR. An IDV-specific qPCR was performed on 232 samples (116 nasal swabs and 116 tracheal washes) that had been previously subject to virome sequencing using MiSeq. Nanopore sequencing was performed on 19 samples positive for IDV by either MiSeq or qPCR. Nanopore sequence data was analyzed by two bioinformatics methods: What’s In My Pot (WIMP, on the EPI2ME platform), and an in-house developed analysis pipeline. The agreement of IDV detection between qPCR and MiSeq was 82.3%, between qPCR and Nanopore was 57.9% (in-house) and 84.2% (WIMP), and between MiSeq and Nanopore was 89.5% (in-house) and 73.7% (WIMP). IDV was detected by MiSeq in 14 of 17 IDV qPCR-positive samples with Cq (cycle quantification) values below 31, despite multiplexing 50 samples for sequencing. When qPCR was regarded as the gold standard, the sensitivity and specificity of MiSeq sequence detection were 28.3% and 98.9%, respectively. We conclude that both MiSeq and Nanopore sequencing are capable of detecting IDV in clinical specimens with a range of Cq values. Sensitivity may be further improved by optimizing sequence data analysis, improving virus enrichment, or reducing the degree of multiplexing. High throughput sequencing is currently revolutionizing the genomics field and providing new approaches to the detection and characterization of microorganisms. The objective of this study was to assess the detection of influenza D virus (IDV) in bovine respiratory tract samples using two sequencing platforms (MiSeq and Nanopore (GridION)), and species-specific qPCR. An IDV-specific qPCR was performed on 232 samples (116 nasal swabs and 116 tracheal washes) that had been previously subject to virome sequencing using MiSeq. Nanopore sequencing was performed on 19 samples positive for IDV by either MiSeq or qPCR. Nanopore sequence data was analyzed by two bioinformatics methods: What's In My Pot (WIMP, on the EPI2ME platform), and an in-house developed analysis pipeline. The agreement of IDV detection between qPCR and MiSeq was 82.3%, between qPCR and Nanopore was 57.9% (in-house) and 84.2% (WIMP), and between MiSeq and Nanopore was 89.5% (in-house) and 73.7% (WIMP). IDV was detected by MiSeq in 14 of 17 IDV qPCR-positive samples with Cq (cycle quantification) values below 31, despite multiplexing 50 samples for sequencing. When qPCR was regarded as the gold standard, the sensitivity and specificity of MiSeq sequence detection were 28.3% and 98.9%, respectively. We conclude that both MiSeq and Nanopore sequencing are capable of detecting IDV in clinical specimens with a range of Cq values. Sensitivity may be further improved by optimizing sequence data analysis, improving virus enrichment, or reducing the degree of multiplexing.High throughput sequencing is currently revolutionizing the genomics field and providing new approaches to the detection and characterization of microorganisms. The objective of this study was to assess the detection of influenza D virus (IDV) in bovine respiratory tract samples using two sequencing platforms (MiSeq and Nanopore (GridION)), and species-specific qPCR. An IDV-specific qPCR was performed on 232 samples (116 nasal swabs and 116 tracheal washes) that had been previously subject to virome sequencing using MiSeq. Nanopore sequencing was performed on 19 samples positive for IDV by either MiSeq or qPCR. Nanopore sequence data was analyzed by two bioinformatics methods: What's In My Pot (WIMP, on the EPI2ME platform), and an in-house developed analysis pipeline. The agreement of IDV detection between qPCR and MiSeq was 82.3%, between qPCR and Nanopore was 57.9% (in-house) and 84.2% (WIMP), and between MiSeq and Nanopore was 89.5% (in-house) and 73.7% (WIMP). IDV was detected by MiSeq in 14 of 17 IDV qPCR-positive samples with Cq (cycle quantification) values below 31, despite multiplexing 50 samples for sequencing. When qPCR was regarded as the gold standard, the sensitivity and specificity of MiSeq sequence detection were 28.3% and 98.9%, respectively. We conclude that both MiSeq and Nanopore sequencing are capable of detecting IDV in clinical specimens with a range of Cq values. Sensitivity may be further improved by optimizing sequence data analysis, improving virus enrichment, or reducing the degree of multiplexing. |
Author | Fernando, Champika Zhang, Maodong Huang, Yanyun Godson, Dale L. Hill, Janet E. Alexander, Trevor W. |
AuthorAffiliation | 1 Department of Veterinary Pathology, Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, SK S7N 5B4, Canada; Maodong.Zhang@usask.ca (M.Z.); yanyun.huang@usask.ca (Y.H.) 4 Agriculture and Agri-Food Canada, Lethbridge Research and Development Centre, Lethbridge, AB T1J 4B1, Canada; trevor.alexander@canada.ca 3 Department of Veterinary Microbiology, Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, SK S7N5B4, Canada; Champika.Fernando@usask.ca 2 Prairie Diagnostic Services Inc., Saskatoon, SK S7N5B4, Canada; dale.godson@usask.ca |
AuthorAffiliation_xml | – name: 2 Prairie Diagnostic Services Inc., Saskatoon, SK S7N5B4, Canada; dale.godson@usask.ca – name: 3 Department of Veterinary Microbiology, Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, SK S7N5B4, Canada; Champika.Fernando@usask.ca – name: 1 Department of Veterinary Pathology, Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, SK S7N 5B4, Canada; Maodong.Zhang@usask.ca (M.Z.); yanyun.huang@usask.ca (Y.H.) – name: 4 Agriculture and Agri-Food Canada, Lethbridge Research and Development Centre, Lethbridge, AB T1J 4B1, Canada; trevor.alexander@canada.ca |
Author_xml | – sequence: 1 givenname: Maodong orcidid: 0000-0002-9565-3017 surname: Zhang fullname: Zhang, Maodong – sequence: 2 givenname: Yanyun surname: Huang fullname: Huang, Yanyun – sequence: 3 givenname: Dale L. orcidid: 0000-0003-1117-5669 surname: Godson fullname: Godson, Dale L. – sequence: 4 givenname: Champika surname: Fernando fullname: Fernando, Champika – sequence: 5 givenname: Trevor W. surname: Alexander fullname: Alexander, Trevor W. – sequence: 6 givenname: Janet E. orcidid: 0000-0002-2187-6277 surname: Hill fullname: Hill, Janet E. |
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CitedBy_id | crossref_primary_10_1371_journal_pone_0267036 crossref_primary_10_1016_j_meegid_2023_105543 crossref_primary_10_1016_j_vetmic_2021_109246 crossref_primary_10_1111_tbed_14085 crossref_primary_10_1186_s12917_022_03269_6 crossref_primary_10_1016_j_scitotenv_2023_166442 crossref_primary_10_1111_tbed_13873 crossref_primary_10_1371_journal_pone_0268957 |
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Keywords | bovine respiratory disease influenza D virus nanopore GridION sequencing diagnostics qPCR Illumina MiSeq sequencing |
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Snippet | High throughput sequencing is currently revolutionizing the genomics field and providing new approaches to the detection and characterization of... |
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SubjectTerms | Animals Antibodies, Viral - blood Bioinformatics bovine respiratory disease Cattle Cattle Diseases - diagnosis Cattle Diseases - virology Computational Biology Dairy cattle Deoxyribonucleic acid diagnostics DNA Enzymes Genome, Viral Genomes high-throughput nucleotide sequencing High-Throughput Nucleotide Sequencing - methods Illumina MiSeq sequencing Influenza Influenza D virus Laboratory animals Library collections Metagenome Metagenomics nanopore GridION sequencing Nanopores Next-generation sequencing nose Orthomyxoviridae Infections - diagnosis Orthomyxoviridae Infections - veterinary Orthomyxoviridae Infections - virology qPCR quantitative polymerase chain reaction Real-Time Polymerase Chain Reaction - methods Respiratory tract Respiratory Tract Infections - diagnosis Respiratory Tract Infections - veterinary Respiratory Tract Infections - virology RNA, Viral - genetics Sensitivity and Specificity Thogotovirus - genetics Thogotovirus - isolation & purification Viruses |
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Title | Assessment of Metagenomic Sequencing and qPCR for Detection of Influenza D Virus in Bovine Respiratory Tract Samples |
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