Abstract
Feline diarrhea is a common digestive tract disease in clinical practice, with watery feces as the main clinical manifestation. There are numerous pathogenic factors causing feline diarrhea, among which viral infections are prevalent, and feline panleukopenia virus (FPV) is the most common pathogen. In recent years, a variety of novel viruses have been detected in the intestines of cats with diarrhea. For example, feline kobuvirus (FKoV) and feline norovirus (FNoV) have been identified. These viruses may have a direct relationship with feline diarrhea or the connection has yet to be discovered. However, with the continuous emergence of these novel viruses and the frequent contact between pet cats and humans, it is prone to large-scale epidemics and outbreaks of viruses. Therefore, developing an accurate, rapid, and simple method to detect novel enteric viruses is of great significance for the early warning of emerging feline enteric viral infectious diseases. A detailed comparison of the genome sequences of the three aforementioned feline enteroviruses was conducted. Subsequently, three pairs of specific primers were designed by selecting the conserved gene regions, and the single and multiplex PCR amplification reaction systems as well as reaction conditions were repeatedly optimized. The target fragment sizes detected by the multiplex PCR method were 650bp for FPV, 500bp for FKoV, and 340bp for FNoV. Sensitivity tests demonstrated that the lower detection limit was one-tenth of that of single PCR. Meanwhile, the detection results for feline calicivirus (FCV), feline herpesvirus (FHV), and feline coronavirus (FCoV) were all negative. Testing of a total of 209 clinical samples from various regions in Shandong Province revealed that the detection rates of the three viruses were 13.4%, 4.8%, and 3.8%, respectively, and mixed infections were present. In this study, an epidemiological investigation of the three feline enteroviruses was performed, and a sensitive, specific, and reproducible multiplex PCR assay was developed, which can be utilized for the detection of clinical samples.
Published Version
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