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Detection and semi-quantitative evaluation of gastrointestinal nematodes in faecal matrices using multiplex real-time PCR assays

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ŠKORPÍKOVÁ Lucie RESLOVÁ Nikol VADLEJCH Jaroslav KAŠNÝ Martin

Rok publikování 2021
Druh Konferenční abstrakty
Fakulta / Pracoviště MU

Přírodovědecká fakulta

Citace
Popis Diagnosis of strongyle nematodes is routinely based on traditional coprological methods involving morphological/morphometric analysis. However, such an approach is laborious, time-consuming, inaccurate, and requires a qualified specialist. Nowadays, molecular methods have become the basis for reliable diagnostics, allowing accurate and efficient identification of nematodes, which is necessary for the implementation of sustainable parasite control strategies. Two multiplex real-time PCR assays for specific detection of six strongyle nematode species, including an internal amplification control to avoid false negative results, were designed. The assays were optimized and verified to detect Haemonchus contortus, Teladorsagia circumcincta, Trichostrongylus colubriformis, Nematodirus battus, Chabertia ovina and Ashworthius sidemi directly from sheep faeces. Semi-quantitative assessment of the infection intensity was enabled using a plasmid construct and a dilutions series of sheep faeces with known numbers of nematode eggs. The assays were performed on 44 individually collected faecal samples from three farms, and the results were compared with those from faecal egg counts using the Concentration McMaster technique and standard larval cultures. Our assays showed great specificity to target species and proved higher sensitivity in strongylid-type egg detection over faecal egg counts techniques, while showing moderate agreement in evaluation of infection intensity. Further, the assays clarified species identification compared to larval cultures. We have proven that our assays are able to analyze faecal samples rapidly and accurately, allowing simultaneous and reliable identification and semi-quantitative estimation of egg numbers.
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