Rapid Detection of Equine Coronavirus by Reverse Transcription Loop-Mediated Isothermal Amplification

J Virol Methods. 2015 Apr;215-216:13-6. doi: 10.1016/j.jviromet.2015.02.001. Epub 2015 Feb 12.

Abstract

A reverse transcription loop-mediated isothermal amplification (RT-LAMP) assay was developed for the rapid detection of equine coronavirus (ECoV). This assay was conducted at 60 °C for 40 min. Specificity of the RT-LAMP assay was confirmed using several equine intestinal and respiratory pathogens in addition to ECoV. The novel assay failed to cross-react with the other pathogens tested, suggesting it is highly specific for ECoV. Using artificially synthesized ECoV RNA, the 50% detection limit of the RT-LAMP assay was 10(1.8)copies/reaction. This is a 50-fold greater sensitivity than conventional reverse transcription polymerase chain reaction (RT-PCR) assays, but a 4-fold lower sensitivity than quantitative RT-PCR (qRT-PCR) assays. Eighty-two fecal samples collected during ECoV outbreaks were analyzed. ECoV was detected in 59 samples using the RT-LAMP assay, and in 30 and 65 samples using RT-PCR or qRT-PCR assays, respectively. Although the RT-LAMP assay is less sensitive than qRT-PCR techniques, it can be performed without the need for expensive equipment. Thus, the RT-LAMP assay might be suitable for large-scale surveillance and diagnosis of ECoV infection in laboratories with limited resources.

Keywords: Diagnosis; Equine coronavirus; RT-PCR; Real-time RT-PCR; Reverse transcription loop-mediated isothermal amplification.

Publication types

  • Comparative Study
  • Evaluation Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Coronavirus / isolation & purification*
  • Coronavirus Infections / diagnosis*
  • Coronavirus Infections / virology*
  • Cross Reactions
  • Feces / virology
  • Horse Diseases / diagnosis*
  • Horse Diseases / virology
  • Horses
  • Molecular Diagnostic Techniques / methods*
  • Nucleic Acid Amplification Techniques / methods*
  • Sensitivity and Specificity
  • Temperature
  • Time Factors