[[Virus-like particle-based immunoglobulin M capture enzyme-linked immunosorbent assay for the detection of IgM antibodies against Chikungunya virus].

Abstract

To establish a MacELISA method for the detection of IgM antibodies against Chikungunya virus (CHIKV), we prepared virus like particle (VLP) antigens of CHIKV using the whole structural protein C-E3-E2-6K-E1 encoding gene with a baculovirus expression system in Sf9 insect cells. The VLPs were purified and used to immunize Kunming mice. Then, polyclonal antibodies were purified from the samples of ascites with a protein G HiTrap SP column and labeled with horseradish peroxidase. A MacELISA method for the detection of IgM antibodies against CHIKV was assembled with goat anti-human IgM antibody, VLP antigens and an enzyme-labeled polyclonal antibody. The results were evaluated with a serum panel containing serum samples from laboratory-confirmed CHIK, HFRS patients, healthy donors, and commercially available CHIKV IgM as a quality control. It was shown that the MacELISA had a specificity of 99% (99/100), the coefficients of variation (CoV) within a plate were <10%, and the CoV of different ELISA plates in terms of the plate variation coefficient was <15%. A comparative analysis was performed to compare the current method against a commercial CHIKV IgM antibody detection kit for IIFA-IgM. The detection limit of MacELISA was significantly lower than that of the IIFA-IgM commercial kit (P< 0.0001). Here, we demonstrate that the VLP-based MacELISA is a promising tool for the early diagnosis and epidemiological investigation of CHIKV infection, with a high level of sensitivity and specificity for the detection of IgM antibodies against CHIKV.

Cite this paper

@article{Li2014ViruslikePI, title={[[Virus-like particle-based immunoglobulin M capture enzyme-linked immunosorbent assay for the detection of IgM antibodies against Chikungunya virus].}, author={Jian-Dong Li and Quan-fu Zhang and Shuo Zhang and Chuan Li and Qin-zhi Liu and Mi-fang Liang and Dexin Li}, journal={Bing du xue bao = Chinese journal of virology}, year={2014}, volume={30 6}, pages={599-604} }