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Archives of Virology

, Volume 161, Issue 6, pp 1485–1491 | Cite as

Generation of E. coli-derived virus-like particles of porcine circovirus type 2 and their use in an indirect IgG enzyme-linked immunosorbent assay

  • Yan Zhang
  • Zhanfeng Wang
  • Yang Zhan
  • Qian Gong
  • Wanting Yu
  • Zhibang Deng
  • Aibing Wang
  • Yi Yang
  • Naidong WangEmail author
Original Article

Abstract

Porcine circovirus type 2 (PCV2) causes increased mortality and poor growth or weight loss in apparently healthy swine. Therefore, methods to detect PCV2-specific antibodies in swine serum are important for prevention, diagnosis, and control of PCV2-associated diseases (PCVAD). In this study, PCV2 virus-like particles (VLPs) were used to develop a rapid, simple and economical indirect enzyme-linked immunosorbent assay to detect (with high sensitivity) PCV2-specific antibodies in swine serum. The PCV2 capsid protein (Cap) was overexpressed in E. coli after optimizing the cap gene. Subsequently, the soluble Cap was rapidly purified in one step by automated fast protein liquid chromatography (FPLC). The purified PCV2 Cap was shown by transmission electron microscopy and gel filtration chromatography to be capable of self-assembling into VLPs in vitro. Using the purified VLPs as antigens, optimal operating conditions for the VLP ELISA were determined. The concentration of PCV2 VLPs was 1 µg/ml per well, and the dilution factors for swine serum and horseradish peroxidase (HRP)-labeled goat anti-pig antibody were 1:150 and 1:4000, respectively. Out of 241 serum samples tested with this assay, 83.4 % were found to be positive. Importantly, the VLP ELISA had a total coincidence rate of 97.4 % (74/76) compared to an Ingezim PCV2 ELISA IgG assay. In summary, this rapid, inexpensive VLP ELISA has the potential to greatly facilitate large-scale investigations of PCV2-associated serotypes.

Keywords

Classical Swine Fever Virus Porcine Circovirus Type PCV2 Infection Swine Serum Baculovirus Expression Vector System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This project was supported by the Research Foundation of Hunan Provincial Education Department, China (grant no. 15A086); Hunan Provincial Natural Science Foundation of China (grant no. 2015JJ2082); Hunan Provincial Natural Science Foundation of China (grants nos. 13JJ1022/S2013J5050); and the General Program of National Natural Science Foundation of China (grants nos. 31270819 and 31372406)

Compliance with ethical standards

Conflict of interest

We declare no conflict of interest.

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Copyright information

© Springer-Verlag Wien 2016

Authors and Affiliations

  • Yan Zhang
    • 1
  • Zhanfeng Wang
    • 1
  • Yang Zhan
    • 1
  • Qian Gong
    • 1
  • Wanting Yu
    • 1
  • Zhibang Deng
    • 1
  • Aibing Wang
    • 1
  • Yi Yang
    • 1
  • Naidong Wang
    • 1
    Email author
  1. 1.Laboratory of Functional Proteomics (LFP) and Research Center of Reverse Vaccinology (RCRV), College of Veterinary MedicineHunan Agricultural UniversityChangshaPeople’s Republic of China

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