Browsing by Author "Gupta SK"

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    A comparative study between milk- and serum-based antibody detection assays for Johne's disease in New Zealand dairy cattle
    (Elsevier B.V., 2025-08-27) Venkatesh KM; Lopez-Villalobos N; Gupta SK; Udy GB; Laven R; Chiu S-J; Bugde P; Furuya Y; Dukkipati VSR
    Dairy cattle are affected by Johne's disease. It is caused by Mycobacterium avium subspecies paratuberculosis (MAP). Suboptimal diagnostic tests add more to the productivity loss resulting from this disease. Agreement between and within different commercial kits is crucial in the decision-making process of disease surveillance programmes. This study compared two ELISAs, that is, Johne's disease commercial antibody detection kits (A and B), using milk and serum samples from New Zealand dairy cattle. These results were also compared with a subset of faecal PCR results. Five scenarios were considered for the comparison of ELISA tests. The point estimates of kappa coefficients (k) between the serum (0.84–0.94) assays were higher than the milk assays (0.59–0.82). The point estimates of kappa coefficients between serum and milk ELISA outcomes were higher for kit B (k = 0.79–0.86) than for kit A (k = 0.55–0.79). The point estimates of kappa coefficients between the ELISA and faecal PCR outcomes varied between 0.43 and 0.74. ELISA tests had point estimates of sensitivity ranging from 0.67 to 0.88 and specificity from 0.62 to 0.93, relative to the faecal PCR test. Results suggest that serum provides a better choice of sample type when both commercial kits A and B are used for Johne's disease surveillance of dairy cattle in New Zealand. Milk assays can be cost-effective to diagnose MAP-positive animals; kit B can be best suited for New Zealand conditions, provided the repeatability of the results is validated.
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    Mapping immunogenic epitopes of an adhesin-like protein from Methanobrevibacter ruminantium M1 and comparison of empirical data with in silico prediction methods.
    (Springer Nature Limited, 2022-06-21) Khanum S; Carbone V; Gupta SK; Yeung J; Shu D; Wilson T; Parlane NA; Altermann E; Estein SM; Janssen PH; Wedlock DN; Heiser A
    In silico prediction of epitopes is a potentially time-saving alternative to experimental epitope identification but is often subject to misidentification of epitopes and may not be useful for proteins from archaeal microorganisms. In this study, we mapped B- and T-cell epitopes of a model antigen from the methanogen Methanobrevibacter ruminantium M1, the Big_1 domain (AdLP-D1, amino acids 19-198) of an adhesin-like protein. A series of 17 overlapping 20-mer peptides was selected to cover the Big_1 domain. Peptide-specific antibodies were produced in mice and measured by ELISA, while an in vitro splenocyte re-stimulation assay determined specific T-cell responses. Overall, five peptides of the 17 peptides were shown to be major immunogenic epitopes of AdLP-D1. These immunogenic regions were examined for their localization in a homology-based model of AdLP-D1. Validated epitopes were found in the outside region of the protein, with loop like secondary structures reflecting their flexibility. The empirical data were compared with epitope predictions made by programmes based on a range of algorithms. In general, the epitopes identified by in silico predictions were not comparable to those determined empirically.