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

Advancements in Research on Duck Tembusu Virus Infections

Duck Tembusu Virus (DTMUV) is a pathogen of the Flaviviridae family that causes infections in poultry, leading to significant economic losses in the duck farming industry in recent years. Ducks infected with this virus exhibit clinical symptoms such as decreased egg production and neurological disorders, along with serious consequences such as ovarian hemorrhage, organ enlargement, and necrosis. Variations in morbidity and mortality rates exist across different age groups of ducks. It is worth noting that DTMUV is not limited to ducks alone; it can also spread to other poultry such as chickens and geese, and antibodies related to DTMUV have even been found in duck farm workers, suggesting a potential risk of zoonotic transmission. This article provides a detailed overview of DTMUV research, delving into its genomic characteristics, vaccines, and the interplay with host immune responses. These in-depth research findings contribute to a more comprehensive understanding of the virus's transmission mechanism and pathogenic process, offering crucial scientific support for epidemic prevention and control.

Leveraging machine learning for taxonomic classification of emerging astroviruses

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.

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

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.

Multiplex digital PCR: a superior technique to qPCR for the simultaneous detection of duck Tembusu virus, duck circovirus, and new duck reovirus

Duck Tembusu virus (DTMUV), duck circovirus (DuCV), and new duck reovirus (NDRV) have seriously hindered the development of the poultry industry in China. To detect the three pathogens simultaneously, a multiplex digital PCR (dPCR) was developed and compared with multiplex qPCR in this study. The multiplex dPCR was able to specifically detect DTMUV, DuCV, and NDRV but not amplify Muscovy duck reovirus (MDRV), Muscovy duck parvovirus (MDPV), goose parvovirus (GPV), H4 avian influenza virus (H4 AIV), H6 avian influenza virus (H6 AIV), and Newcastle disease virus (NDV). The standard curves showed excellent linearity in multiplex dPCR and qPCR and were positively correlated. The sensitivity results showed that the lowest detection limit of multiplex dPCR was 1.3 copies/μL, which was 10 times higher than that of multiplex qPCR. The reproducibility results showed that the intra- and interassay coefficients of variation were 0.06-1.94%. A total of 173 clinical samples were tested to assess the usefulness of the method; the positive detection rates for DTMUV, DuCV, and NDRV were 18.5, 29.5, and 14.5%, respectively, which were approximately 4% higher than those of multiplex qPCR, and the kappa values for the clinical detection results of multiplex dPCR and qPCR were 0.85, 0.89, and 0.86, indicating that the two methods were in excellent agreement.