DETECTION OF CRYPTOSPORIDIUM ANTIBODIES IN SERA AND ORAL FLUIDS USING MULTIPLEX BEAD ASSAY*
- 1 April 2004
- journal article
- research article
- Published by American Society of Parasitologists in Journal of Parasitology
- Vol. 90 (2) , 397-404
- https://doi.org/10.1645/ge-3267
Abstract
For the first time, a multiplex bead assay (MBA) was used to assay oral fluid and serum specimens for immunoglobulin G (IgG) antibodies to specific Cryptosporidium parvum antigens that were coupled to polystyrene beads. Recombinant C. parvum 17- and 27-kDa antigens (r17 and r27, respectively) both linked with glutathione-S-transferase (GST) fusion proteins, native 17-kDa antigen, and GST alone were each coupled to microspheres that could be differentiated based on variable amounts of internally incorporated red fluorescent dye. Initial and follow-up serum and oral fluid specimens from a 1997 cryptosporidiosis outbreak in Spokane, Washington, were incubated with the coupled beads. Antibodies bound to the coupled beads were detected using biotinylated monoclonal anti-human IgG antibody and streptavidin-labeled r-phycoerythrin. Fluorescence intensity was measured by flow cytometry. For the 3 C. parvum antigens, the median of the mean fluorescence intensity (MFI) was significantly higher (P < 0.03) in the initial specimens than in the follow-up specimens. No significant change in IgG responses to GST in oral fluids or serum specimens was observed. For all Cryptosporidium antigens, the MFI in the initial serum specimens correlated with the MFI in the initial oral fluid specimens (P < 0.001, r > 0.673). For the recombinant antigens used in the MBA, the MFI correlated with the response as measured by an enzyme-linked immunosorbent assay that used r17 and r27 expressed without the GST fusion partner (P < 0.001, r > 0.854). MBA using sera or more conveniently collected oral fluids, especially from children, may be an option for immunodiagnosis of C. parvum infection and for prospective epidemiological studies designed to monitor infection risk.Keywords
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