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Background: Aleutian mink disease, mink viral enteritis and canine distemper are known as the three most serious diseases that cause great economic loss in the mink industry. In clinical practice, aleutian mink disease virus (AMDV), mink enteritis virus (MEV) and canine distemper virus (CDV) are common mixed infections, and they have similar clinical symptoms, such as diarrhoea. Therefore, a rapid and accurate differential diagnosis method for use on mink ranches is essential for the control of these three pathogens. Here, we developed multiplex one-step real-time quantitative PCR (RT‒qPCR) assays for the simultaneous detection and quantification of AMDV, MEV and CDV by using three primers and probes based on the conserved NS1, VP2 and N genes, respectively. Results: The results showed that the established method was less likely to cross-react with other mink pathogens, with a detection sensitivity of 25 copies/μL and a coefficient of variation less than 3.51%. Moreover, the interference experiment showed that the presence of AMDV, MEV and CDV templates at different concentrations would not interfere with the detection results. Furthermore, two hundred clinical samples of mink with diarrhoea were simultaneously analysed using multiplex RT‒qPCR and single RT‒qPCR, the Kappa values were all greater than 0.921, indicating that there was a high degree of coincidence between the two detection methods. Conclusions: In conclusion, multiplex RT‒qPCR exhibited high specificity, sensitivity, and reproducibility, indicating that this method can be used as a reliable and specific tool for the differential detection and quantification of AMDV, MEV and CDV.
Background: Aleutian mink disease, mink viral enteritis and canine distemper are known as the three most serious diseases that cause great economic loss in the mink industry. In clinical practice, aleutian mink disease virus (AMDV), mink enteritis virus (MEV) and canine distemper virus (CDV) are common mixed infections, and they have similar clinical symptoms, such as diarrhoea. Therefore, a rapid and accurate differential diagnosis method for use on mink ranches is essential for the control of these three pathogens. Here, we developed multiplex one-step real-time quantitative PCR (RT‒qPCR) assays for the simultaneous detection and quantification of AMDV, MEV and CDV by using three primers and probes based on the conserved NS1, VP2 and N genes, respectively. Results: The results showed that the established method was less likely to cross-react with other mink pathogens, with a detection sensitivity of 25 copies/μL and a coefficient of variation less than 3.51%. Moreover, the interference experiment showed that the presence of AMDV, MEV and CDV templates at different concentrations would not interfere with the detection results. Furthermore, two hundred clinical samples of mink with diarrhoea were simultaneously analysed using multiplex RT‒qPCR and single RT‒qPCR, the Kappa values were all greater than 0.921, indicating that there was a high degree of coincidence between the two detection methods. Conclusions: In conclusion, multiplex RT‒qPCR exhibited high specificity, sensitivity, and reproducibility, indicating that this method can be used as a reliable and specific tool for the differential detection and quantification of AMDV, MEV and CDV.
Background: The issue of Helicobacter pylori (H. pylori) resistance to clarithromycin (CLR) has consistently posed challenges for clinical treatment. Hence, a rapid susceptibility testing (AST) method urgently needs to be developed. Methods: In the present study, 35 isolates of H. pylori were isolated from 203 gastritis patients of the Guangzhou cohort, and the antimicrobial resistance phenotypes were associated with their genomes to analyze the relevant mutations. Based on these mutations, a rapid detection system utilizing high-resolution melting (HRM) curve analysis was designed and verified by the Shenzhen cohort, which consisted of 38 H. pylori strains. Results: Genomic analysis identified the mutation of the 2143 allele from A to G (A2143G) of 23S rRNA as the most relevant mutation with CLR resistance (p < 0.01). In the HRM system, the wild-type H. pylori showed a melting temperature (Tm) of 79.28 ± 0.01 °C, while the mutant type exhibited a Tm of 79.96 ± 0.01 °C. These differences enabled a rapid distinction between two types of H. pylori (p < 0.01). Verification examinations showed that this system could detect target DNA as low as 0.005 ng/μL in samples without being affected by other gastric microorganisms. The method also showed a good performance in the Shenzhen validation cohort, with 81.58% accuracy, and 100% specificity. Conclusions: We have developed an HRM system that can accurately and quickly detect CLR resistance in H. pylori. This method can be directly used for the detection of gastric microbiota samples and provides a new benchmark for the simple detection of H. pylori resistance.
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