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Establishment of a rapid detection method for plutella xylostella granulovirus based on qPCR. | LitMetric

AI Article Synopsis

  • Plutella xylostella granulovirus (PlxyGV) is a biopesticide that effectively controls damage to cruciferous vegetables caused by the pest Plutella xylostella.
  • In China, PlxyGV production has been scaled up using host insects since its registration in 2008, but traditional counting methods for the virus particles (using optical microscopy) face challenges due to particle size and other factors.
  • The study introduces an optimized Real-time fluorescence quantitative PCR (qPCR) method for accurate and repeatable quantification of PlxyGV occlusion bodies, enhancing the reliability of its production and application.

Article Abstract

Plutella xylostella granulovirus (PlxyGV) biopesticide is an effective tool to control the long-term damage of Plutella xylostella (Linnaeus) to cruciferous vegetables. In China, PlxyGV can be produced on a large scale using host insects, and its products have been registered in 2008. In experiments and biopesticide production, the routine enumeration method of PlxyGV virus particles is to use the Petroff-Hausser counting chamber in dark field microscope. However, the accuracy and repeatability of granulovirus (GV) counting are affected due to the small particle size of GV occlusion bodies (OBs), the limitations of optical microscope, the judgment of different operators, host impurities, the addition of biological products. This limits the convenience of its production, product quality, trading and field application. Here we use PlxyGV as an example, the method based on Real-time fluorescence quantitative PCR (qPCR) was optimized from two aspects of sample treatment and specific primers design, which improved the repeatability and accuracy of absolute quantitative OBs of GV. This study provides basic information for accurate quantitative PlxyGV by qPCR method.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10122022PMC
http://dx.doi.org/10.1016/j.heliyon.2023.e15170DOI Listing

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