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Scientific reports · 2025

Candidate serum metabolite biomarkers of subclinical Haemonchus contortus infection in sheep.

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Jawad Hamza, Gellatly Desiree, Lei Yaogeng, Thompson Sean, Borzouie Shima, Osonowo Olufemi, Gilleard John S, Miar Younes, Goldansaz Seyed Ali, Manafiazar Ghader

Аннотация

Parasitic infection is a major factor negatively affecting sheep production worldwide. The gold standard, fecal egg count, identifies only clinical stages after egg count establishment and shedding in the feces. However, detection at the sub-clinical phase could offer a critical window for strategic deworming and prevent production losses. Blood metabolites often perform as signalling molecules preceding major physiological events; thus, they could provide a prognosis of immunological alterations in the host. Therefore, we conducted a controlled longitudinal study to identify predictive biomarkers of Haemonchus contortus infection in 60 Rideau Arcott ewe lambs, analyzing 420 serum samples across seven timepoints (from one day pre-inoculation to 57-days post-inoculation [dpi]) using direct injection mass spectrometry and reverse-phase liquid chromatography-tandem mass spectrometry custom assay. We identified a total of 22 unique metabolites as candidate biomarkers of parasitic infection pre- and post-drenching, ranging in area-under-the-receiver-operating-characteristic-curve (AU-ROC) values 0.69–0.94 (p < 0.05). The earliest candidate biomarkers were detectable at 7-dpi, the most promising pre-drenching biomarkers emerged at 21-dpi, while the highest AU-ROC value post-drenching was at 42-dpi. This is the first study to identify predictive blood biomarkers of H. contortus infection in Rideau Arcott ewe lambs, including the relevant mathematical models. Further validation in larger cohorts could lead to a simple blood test for sub-clinical parasite infection detection, reducing anthelmintic use on sheep farms.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты