Development of a new immunochromatographic strip mediated by colloidal Gold-MAb nanoparticles for rapid detection of subgroup K Avian leukemia virus

K subgroup of Avian leukemia virus (ALV-K), as the latest reported exogenous ALV subgroup, can cause severe immunosuppression and tumorigenesis in infected chickens and bring serious threats to the poultry. Culling the positive chickens from breeder flocks is the most effective measurement for controling its infection at present. To setup a specific and rapid method for detecting ALV-K, an immunochromatographic strip (ICS) based on colloidal gold nanoparticles and double monoclonal antibodies (MAbs) immunochemical reaction was successfully developed. The solution containing colloidal gold particles (colloidal 20 nm) was prepared by sodium citrate reduction, and the ascites MAbs against ALV-K were purified and identified. The antibody concentration of the colloidal gold-MAb complex reaction system was 9.6 mu g/mL, and the optimum pH was 7.5. The optimum coating concentrations of the captured antibody and quality control antibody on the NC membrane were 1.2 mg/mL and 0.6 mg/mL, respectively. The results showed that the prepared ICS could specifically detect ALV-K and had no cross reaction with exogenous ALV-A/B/J strains. Its sensitivity was 64 TCID50/mL against ALV-K and 0.25 mu g/ mL against ALV-K gp85 protein. The ICS stored at 4 degree celsius for 180 d, at 25 degree celsius for 45 d, and at 37 degree celsius for 15 d could stably detect ALV-K in the samples. In comparision detection of 128 clinical samples, the coincidence rates in cloacal swab samples, serum samples, egg albumen samples and tissue homogenate samples between the ICS and the commercial ALV p27 antigen ELISA kit were 100 %, 100 %, 96.7 % and 96.9 %, respectively; moreover, the prepared ICS in operations was simpler and more convenient. This study supplies a new specific and rapid method for detecting ALV-K in clinics. This is the first report on the application of nano-colloidal gold ICS in ALVK differential detection.