Rapid diagnosis of duck Tembusu virus and goose astrovirus with TaqMan-based duplex real-time PCR

Li, Haiqin; Wan, Chunhe; Wang, Zhangzhang; Tan, Jiafu; Tan, Meifang; Zeng, Yanbing; Huang, Jiangnan; Huang, Yu; Su, Qi; Kang, Zhaofeng; Guo, Xiaoquan

doi:10.3389/fmicb.2023.1146241

Cited by 7 publications

(9 citation statements)

References 21 publications

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“…Second, our RT-LAMP-based CRISPR-Cas12a assay has higher specificity than RT-LAMP solely because the Cas12a-crRNA complex specifically recognizes the target gene and discriminates nucleotide mismatches to avoid false-positive results ( Chen J. S. et al, 2018 ). Third, our assay detects DTMUV RNA with a limited detection of 3 copies/μL, which is more sensitive than reported qPCR assays of DTMUV, including the SYBR Green qPCR assay (100 copies/μL) in our study ( Yan L. P. et al, 2011 ; Yan et al, 2012 ; Yun et al, 2012 ; Wan et al, 2016 ; Chen G. Q. et al, 2018 ; Zhang et al, 2020 ; Li et al, 2023 ). Fourth, our assay can be completed within 2 h from RNA extraction to readout, which suggests that our assay is more suitable for rapid detection of DTMUV relative to conventional PCR and qPCR.…”

Section: Discussionmentioning

confidence: 67%

“…Compared with them, the qPCR assays achieve high-throughput pathogen detection and provide a real-time readout via the qPCR instrument. Currently, some qPCR assays, such as one-step RT-qPCR assay targeting the 3′ terminal noncoding region (NCR), TaqMan-based qPCR assays targeting the E or NS1 gene and SYBR Green qPCR assay targeting the E gene, have been exploited to detect DTMUV RNA or cDNA, and these assays have limits of detection from 10 to 2.67 × 10 2 copies/μL ( Yan L. P. et al, 2011 ; Yan et al, 2012 ; Yun et al, 2012 ; Wan et al, 2016 ; Chen G. Q. et al, 2018 ; Zhang et al, 2020 ; Li et al, 2023 ). Nonetheless, both PCR-based assays and qPCR assays take at least 2 to 4 h and require special equipment, which suggests that they are not convenient for the field detection of DTMUV.…”

Section: Discussionmentioning

confidence: 99%

“…Currently, several PCR-based assays, targeting the E , NS3 and NS5 genes have been established for DTMUV detection ( Zang et al, 2012 ; Li, 2013 ; Wang et al, 2017 ). In addition, some qPCR-based assays targeting the E , NS1 and 3′-NCR genes were also exploited to detect DTMUV ( Yan et al, 2012 ; Yun et al, 2012 ; Chen G. Q. et al, 2018 ; Li et al, 2023 ). However, these PCR-based and qPCR-based assays are mainly applied to laboratory testing of DTMUV.…”

Section: Introductionmentioning

confidence: 99%

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Development of a reverse transcription loop-mediated isothermal amplification based clustered regularly interspaced short palindromic repeats Cas12a assay for duck Tembusu virus

Ding,

Huang,

et al. 2023

Front. Microbiol.

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Duck Tembusu virus (DTMUV) is an emerging pathogen that poses a serious threat to the duck industry in China. Currently, polymerase chain reaction (PCR), quantitative PCR (qPCR) and reverse transcription loop-mediated isothermal amplification (RT-LAMP) are commonly used for DTMUV detection. However, these methods require complex steps and special equipment and easily cause false-positive results. Therefore, we urgently need to establish a simple, sensitive and specific method for the clinical field detection of DTMUV. In this study, we developed an RT-LAMP-based CRISPR-Cas12a assay targeting the C gene to detect DTMUV with a limited detection of 3 copies/μL. This assay was specific for DTMUV without cross-reaction with other common avian viruses and only required some simple pieces of equipment, such as a thermostat water bath and blue/UV light transilluminator. Furthermore, this assay showed 100% positive predictive agreement (PPA) and negative predictive agreement (NPA) relative to SYBR Green qPCR for DTMUV detection in 32 cloacal swabs and 22 tissue samples, supporting its application for clinical field detection.

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Section: Discussionmentioning

confidence: 67%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Development of a reverse transcription loop-mediated isothermal amplification based clustered regularly interspaced short palindromic repeats Cas12a assay for duck Tembusu virus

Ding,

Huang,

et al. 2023

Front. Microbiol.

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“…One of the most common methods of SNP genotyping with qPCR is the TaqMan method [16,24]. This method remains one of the most commonly used in genotyping today [25][26][27]. This method is ideal for genotyping known polymorphisms that are allele specific in a given genome.…”

Section: Taqman Methodsmentioning

confidence: 99%

Agrigenomic Diversity Unleashed: Current Single Nucleotide Polymorphism Genotyping Methods for the Agricultural Sciences

Lawrie,

Massey

2023

Applied Biosciences

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Single Nucleotide Polymorphisms (SNPs) are variations that occur at single nucleotides in the genome and are present at an appreciable level in a population. SNPs can be linked to phenotypes of interest, for example diseases, recent adaptations, or species hybridization. They can also be used to study phylogeny and evolutionary history. Technologies that rapidly identify and catalog the presence of SNPs in a DNA sample are known as SNP genotyping panels, and they continue to undergo rapid development. Such methods have great utility across the agricultural sciences in diverse areas such as plant and animal breeding, pathogen and pesticide resistance identification, outbreak tracing, and hybridization detection. Here, we provide an overview of 14 different SNP genotyping technologies and weigh some of the pros and cons associated with each platform. This review is not comprehensive or technical, nor does it aim to be. Rather, the objective is to provide an introduction to the landscape of genotyping technologies for researchers who do not have experience with these methods. Three classes of SNP genotyping methods are Polymerase Chain Reaction (PCR)-based (nine different methods), microarray-based (one method), and Next-Generation Sequencing (NGS)-based (four different methods). We discuss how each genotyping class is suited for different niches; PCR-based has a low SNP count and high sample number, microarray-based has a very high SNP count and a moderate sample number, and Next-Generation Sequencing-based has a moderate SNP count and moderate number of samples. Included are basics about how the methods function and example use cases of each method. Additionally, we introduce and discuss the potential for the MinION sequencer in SNP genotyping. For each technology, we provide insights into cost, equipment needs, labor costs, experimental complexity, data output complexity, and accessibility. These considerations address the feasibility of deploying the technologies in an agricultural science environment.

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“…Astroviruses are a genetically diverse virus family notably responsible for the second most common cause of nosocomial diarrhea following rotaviruses ( Meyer et al, 2015 ), as well as substantial economic losses in the poultry industry ( Karlsson et al, 2015 ; Li et al, 2023 ). Also, astrovirus infection has been associated with encephalitis and meningitis in immunocompromised patients ( Vu et al, 2017 ) and astrovirus infection has been shown to be present in the brains of some mammals ( Chae et al, 2023 ).…”

Section: Introductionmentioning

confidence: 99%

Leveraging machine learning for taxonomic classification of emerging astroviruses

Alipour,

Holmes,

et al. 2024

Front. Mol. Biosci.

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Astroviruses are a family of genetically diverse viruses associated with disease in humans and birds with significant health effects and economic burdens. Astrovirus taxonomic classification includes two genera, Avastrovirus and Mamastrovirus. However, with next-generation sequencing, broader interspecies transmission has been observed necessitating a reexamination of the current host-based taxonomic classification approach. In this study, a novel taxonomic classification method is presented for emergent and as yet unclassified astroviruses, based on whole genome sequence k-mer composition in addition to host information. An optional component responsible for identifying recombinant sequences was added to the method’s pipeline, to counteract the impact of genetic recombination on viral classification. The proposed three-pronged classification method consists of a supervised machine learning method, an unsupervised machine learning method, and the consideration of host species. Using this three-pronged approach, we propose genus labels for 191 as yet unclassified astrovirus genomes. Genus labels are also suggested for an additional eight as yet unclassified astrovirus genomes for which incompatibility was observed with the host species, suggesting cross-species infection. Lastly, our machine learning-based approach augmented by a principal component analysis (PCA) analysis provides evidence supporting the hypothesis of the existence of human astrovirus (HAstV) subgenus of the genus Mamastrovirus, and a goose astrovirus (GoAstV) subgenus of the genus Avastrovirus. Overall, this multipronged machine learning approach provides a fast, reliable, and scalable prediction method of taxonomic labels, able to keep pace with emerging viruses and the exponential increase in the output of modern genome sequencing technologies.

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Rapid diagnosis of duck Tembusu virus and goose astrovirus with TaqMan-based duplex real-time PCR

Cited by 7 publications

References 21 publications

Development of a reverse transcription loop-mediated isothermal amplification based clustered regularly interspaced short palindromic repeats Cas12a assay for duck Tembusu virus

Development of a reverse transcription loop-mediated isothermal amplification based clustered regularly interspaced short palindromic repeats Cas12a assay for duck Tembusu virus

Agrigenomic Diversity Unleashed: Current Single Nucleotide Polymorphism Genotyping Methods for the Agricultural Sciences

Leveraging machine learning for taxonomic classification of emerging astroviruses

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