Development of RT-RPA-based point-of-care tests for epidemic arthritogenic alphaviruses

Insights

New point-of-care diagnostic tests for Chikungunya (CHIKV), o'nyong-nyong (ONNV), and Mayaro (MAYV) viruses offer rapid and specific detection. These recombinase polymerase amplification (RPA) tests can identify 10 viral copies in 20 minutes, improving arboviral infection management.

Area of Science:

  • Medical Entomology
  • Virology
  • Molecular Diagnostics

Background:

  • Chikungunya (CHIKV), o'nyong-nyong (ONNV), and Mayaro (MAYV) are mosquito-borne alphaviruses causing arthritogenic syndromes, with outbreaks in tropical and subtropical regions.
  • Existing diagnostics like ELISAs lack specificity due to cross-reactivity, while qPCR requires specialized laboratory equipment.
  • There is a critical need for sensitive, specific, and accessible point-of-care (POC) diagnostics for these emerging arboviruses.

Purpose of the Study:

  • To develop and validate sensitive, virus-specific point-of-care (POC) diagnostic tests for CHIKV, ONNV, and MAYV.
  • To assess the utility of recombinase polymerase amplification (RPA) for rapid alphavirus detection.
  • To evaluate the clinical applicability of RPA tests in animal models and human patients.

Main Methods:

  • Development of three distinct RPA-based assays targeting CHIKV, ONNV, and MAYV.
  • Validation of RPA test sensitivity (limit of detection) and specificity (cross-reactivity).
  • Testing of RPA assays on serum and tissue samples from infected mice and humans.

Main Results:

  • Developed virus-specific RPA POC tests for CHIKV, ONNV, and MAYV.
  • Tests achieved high sensitivity, detecting 10 viral copies within 20 minutes without cross-reactivity.
  • RPA assays successfully detected viruses in clinical samples, and amplicons were sequenceable for epidemiological studies.

Conclusions:

  • These rapid and specific RPA-based POC diagnostics significantly improve early detection and management of CHIKV, ONNV, and MAYV infections.
  • The technology facilitates molecular epidemiological studies, aiding in understanding arboviral disease spread.
  • The findings underscore the potential of RPA for decentralized diagnostics in resource-limited settings.