Estimation of serum antibody to subgingival species using checkerboard immunoblotting
- 1 October 1997
- journal article
- research article
- Published by Wiley in Oral Microbiology and Immunology
- Vol. 12 (5) , 303-310
- https://doi.org/10.1111/j.1399-302x.1997.tb00395.x
Abstract
Measurement of serum antibody to subgingival bacterial species has been useful in discriminating possible periodontal pathogens and in assessing the host's immune response to subgingival species. An immunoassay system was developed to measure the level of serum antibody to multiple subgingival species in multiple serum samples on a single nitrocellulose membrane. The principle steps of the assay are the following: 1) binding of antigens from bacterial preparations and protein A in parallel lanes on nitrocellulose membranes; 2) incubation of known concentrations of human immunoglobulin as well as various dilutions of serum from patients in lanes perpendicular to the antigen lanes; 3) incubation of the membrane with a peroxidase‐conjugated second antibody; 4) detection of positive reactions by enhanced chemilurninescence. Emitted light was captured on a photographic film in which the positive reactions appeared as squares at the intersections of antigens with appropriate antibody. Antibody was quantified using a laser densitometer to compare the signal intensity of unknown samples with the ones generated by known amounts of human immunoglobulin captured on the same membrane. The assay permitted simultaneous screening and/or quantification of antibody in as many as 45 serum samples against up to 45 bacterial species. The mean and standard error of the coefficients of variation for replicates within an assay averaged 7.3±2.3%. Coefficients of variation of the assay run on different days for serum antibody to a range of subgingival species averaged 10.1 ±2.1%. Checkerboard immunoblotting is a simple and rapid immunoassay to permit quantification and/or screening of antibody to multiple subgingival species or antigens in multiple serum samples.Keywords
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