A multiplex real-time fluorescence-based quantitative PCR assay for calf diarrhea viruses

Abstract

IntroductionCalf diarrhea is a significant condition that has a strong effect on the cattle industry, resulting in huge economic losses annually. Bovine torovirus (BToV), bovine enterovirus (BEV), bovine norovirus (BNoV), bovine coronavirus (BCoV), bovine rotavirus (BRV), and bovine viral diarrhea virus (BVDV) are key pathogens that have been implicated in calf diarrhea. Among these viruses, there remains limited research on BToV, BEV, and BNoV, with no available vaccines or drugs for their prevention and control. Although commercial vaccines exist for BCoV, BRV, and BVDV, the prevalence of these diseases remains high.MethodsTo address this issue, we developed a multiplex real-time fluorescence quantitative PCR method for detecting BToV, BEV, BNoV, BCoV, BRV, and BVDV. This method can be used to effectively monitor the prevalence of these six viruses and serve as a reference for future prevention and control strategies. In this study, we specifically designed primers and probes for the BNoV Rdrp, BEV 5′UTR, BToV M, BCoV N, BRV NSP5, and BVDV 5′UTR genes.ResultsThis method was determined to be efficient, stable, and sensitive. The lowest detectable levels of plasmids for BNoV, BEV, BToV, BRV, BCoV, and BVDV were 1.91 copies/μL, 96.0 copies/μL, 12.8 copies/μL, 16.4 copies/μL, 18.2 copies/μL, and 65.3 copies/μL, respectively. Moreover, the coefficients of variation for all six detection methods were < 3%; they also exhibited a strong linear relationship (R2 ≥ 0.98), and an amplification efficiency of 90%−110%. A total of 295 fecal and anal swabs were collected from calves with diarrhea in Guangdong, China. The positive rates for BToV, BEV, BNoV, BCoV, BR, and BVDV were determined to be 0.34% (1/295), 6.10% (18/295), 0.68% (2/295), 1.36% (4/295), 10.85% (32/295), and 2.03% (6/295), respectively. Notably, BEV and BRV exhibited the highest prevalence.DiscussionAdditionally, this study identified the occurrence of BToV and BNoV in Guangdong for the first time. In summary, this study successfully established an effective method for detecting several important bovine viruses; ultimately, this holds strong implications for the future development of the cattle industry.