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Optimization and validation of ELISAs for interferon-gamma determination in bison
Josephine Chileshe1, Todd Shury2, Jeffrey M Chen1
1Vaccine and Infectious Disease Organization (VIDO), University of Saskatchewan, Saskatoon, Saskatchewan, Canada.
Early detection of bovine tuberculosis in wood bison is crucial for conservation. Optimized interferon-gamma (IFNγ) assays show promise for diagnosing Mycobacterium bovis infection in bison, aiding disease management.
Area of Science:
- Wildlife disease ecology
- Immunodiagnostics
- Conservation medicine
Background:
- Bovine tuberculosis (bTB), caused by Mycobacterium bovis, is a significant threat to wood bison conservation in Canada.
- Early detection of M. bovis is vital to prevent transmission and protect this culturally and ecologically important species.
- Interferon-gamma (IFNγ) assays are established diagnostic tools for bTB in cattle and other wildlife.
Purpose of the Study:
- To optimize and partially validate two commercial IFNγ ELISA kits for detecting endogenous bison IFNγ.
- To assess the diagnostic potential of these assays in wood bison populations.
Main Methods:
- Evaluation of antibody identification, matrix effects, dilution linearity, and assay reproducibility.
- Optimization of two commercial IFNγ ELISA kits (Mabtech bovine Flex and Pro).
- Testing of mitogen-stimulated whole blood samples from bison.
Main Results:
- Optimized assays showed linear responses to recombinant bovine and endogenous bison IFNγ (1-125 pg/mL; R²=0.99).
- Assays exhibited good recovery and fair reproducibility with a low limit of quantification (1 pg/mL).
- Both Mabtech Flex and Pro kits were deemed suitable for measuring bison IFNγ.
Conclusions:
- Commercial IFNγ ELISA kits can be effectively optimized for diagnosing M. bovis infection in wood bison.
- These validated assays offer a flexible tool for early detection and management of bovine tuberculosis in bison populations.
- Improved diagnostic capabilities are essential for the conservation of wood bison and mitigating zoonotic risks.
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