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Evaluation of an automated magnetic bead-based DNA extraction and real-time PCR in fecal samples as a pre-screening test for detection of Echinococcus multilocularis and Echinococcus canadensis in coyotes

Author:
Santa, Maria A., Pastran, Sonya, Klein, Claudia, Ruckstuhl, Kathreen, Massolo, Alessandro
Source:
Parasitology research 2019 v.118 no.1 pp. 119-125
ISSN:
0932-0113
Subject:
Canis latrans, DNA, Echinococcus multilocularis, Elymus canadensis, adults, automation, diagnostic sensitivity, diagnostic techniques, feces, filtration, magnetism, mixed infection, monitoring, parasites, quantitative polymerase chain reaction, Canada
Abstract:
Efficient and sensitive diagnostic tools are essential for the study of the eco-epidemiology of Echinococcus species. We evaluated an automated magnetic bead-based DNA extraction commercial kit followed by qPCR (MB-qPCR), for the detection of Echinococcus multilocularis and Echinococcus canadensis in coyote (Canis latrans) fecal samples. The diagnostic sensitivity was determined by validating the method against the scraping, filtration, and counting technique (SFCT) for samples collected in Canada. From the 60 samples tested, 27 out of 31 SFCT positives samples for Echinococcus cestodes were positive in the MB-qPCR for E. multilocularis, with a sensitivity of 87.1% (95% CI 70.2 to 96.4%). Two samples were also positive for E. canadensis in the MB-qPCR and confirmed by morphological identification of adult worms. The agreement of the MB-qPCR and the SFCT was statistically significant with a kappa value of 0.67 (95% CI 0.48–0.85; p value < 0.001). The magnetic bead-based DNA extraction followed by qPCR proved to have a sensitivity comparable to the SFCT to detect E. multilocularis. Although the diagnostic sensitivity for E. canadensis was not estimated, MB-qPCR identified E. canadensis cases previously overlooked when using SFCT. We propose a combination of molecular and morphological identification using the MB-qPCR and the SFCT to detect both parasites, allowing for a more efficient large-scale surveillance, and detecting co-infections of Echinococcus species that can be difficult to identify when only based on morphology.
Agid:
6272746