Abstract

Lychnis mottle virus (LycMoV; genus Unassigned, family Secoviridae) infection of Angelica sinensis produces mottle and mosaic symptoms, damaging the host. Early detection of relevant pathogens is the most critical step in preventing the potential transmission of infectious disease. Polyclonal antibodies (pAbs) with high potency and high specificity were prepared using the recombinant LycMoV capsid protein as an antigen. Here, we developed and optimized a rapid colloidal gold immunochromatography assay (GICA) detection system for LycMoV using this antibody. Under optimum conditions, GICA specifically detected (up to 10,000-fold) positive LycMoV samples. A real-time reverse transcription loop-mediated isothermal amplification (RT-LAMP) system was also established by selecting the primers with high sensitivity and specificity to LycMoV. The RT-LAMP detection threshold was 1.42 fg/μl (291 copies/μl). A GICA-RT-LAMP assay system was further established and optimized. The minimum GICA detection line was calculated at 1.52x10-2 ng/μl. Although GICA did not detect positive samples after capturing 2.53x10-3 ng/μl of virus, GICA-LAMP and GICA-RT-PCR did, whose sensitivity was comparatively greater than six-fold. This is the first report showing that GICA-RT-LAMP is a cost effective approach for use in detecting LycMoV without extracting nucleic acids. These sensitive assays will help improve virus disease management in A. sinensis crops.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.