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Journal of Immunological Methods 2007-Jul

A novel automated method for enumeration of Chlamydia trachomatis inclusion forming units.

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Su Wang
Lani Indrawati
Melissa Wooters
Ivette Caro-Aguilar
Jodie Field
Robin Kaufhold
Angela Payne
Michael J Caulfield
Jeffrey G Smith
Jon H Heinrichs

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Abstracto

Chlamydia trachomatis is an obligate intracellular pathogen that primarily infects epithelial cells. Traditional methods for quantification of inclusion forming units (IFUs) rely upon infection of epithelial cell monolayers in vitro. Following incubation for approximately 2 days, inclusion bodies that result from infection of cells are detected by immunofluorescent staining with an antibody conjugated to a fluorescent dye. These inclusion bodies are then manually counted by microscopic examination of multiple, randomly selected fields of view. This requires substantial operator time and is subject to investigator bias. We have developed a novel method in which we utilize an automated microplate ImmunoSpot reader to count C. trachomatis IFUs. Following infection of epithelial cells in a 96-well plate and subsequent incubation, IFUs are fixed and detected with an anti-C. trachomatis LPS monoclonal antibody. Immobilized antibody is detected with a biotinylated secondary antibody and visualized enzymatically with streptavidin-alkaline phosphatase and the colorimetric substrate nitro-blue tetrazolium chloride/5-bromo-4-chloro-3-indolyl-phospate (NBT/BCIP). IFUs are then enumerated with the ImmunoSpot system. This method has been used to quantify IFUs from all cell lines traditionally used for chlamydial propagation, including L929, McCoy, HeLa and HaK cells. IFU numbers obtained are comparable to those determined by traditional microscopic counting. In addition, the method can be applied to rapid determination of serum-neutralizing titers for vaccine studies, and we have also applied this approach to quantify Chlamydia recovered from vaginal swabs collected from infected animals. This method provides for rapid enumeration of IFU counts while minimizing investigator bias and has potential applications for both research and diagnostic use.

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