Abstract
Objectives
We aimed to develop a reverse transcription loop-mediated isothermal amplification (RT-LAMP) platform for the rapid detection of CHIKV in both patient and mosquito samples from Brazil.
Methods
We optimized an RT-LAMP assay, then evaluated the sensitivity and specificity using visual detection. In comparison with the RT-qPCR reference method, we validated the utility of this assay as a molecular diagnostic test in a reference laboratory for arbovirus diagnostics using 100 serum samples collected from suspected CHIKV cases.
Results
Our RT-LAMP assay specifically detected CHIKV without cross-reactivity against other arboviruses. The limit of detection of our RT-LAMP was estimated in −1.18 PFU (confidence interval [CI] ranging from -2.08 to 0.45), resulting in a similar analytical sensitivity when directly compared to the gold standard RT-qPCR assay. Then, we demonstrate the ability of our RT-LAMP assay to detect the virus in different human specimens (serum, urine, and saliva), and crude lysate of Aedes aegypti mosquitoes in as little as 20-30 minutes and without a separate RNA isolation step. Lastly, we showed that our RT-LAMP assay could be lyophilized and reactivated by adding water, indicating potential for room-temperature storage. Our RT-LAMP had a clinical sensitivity of 100% (95% CI, 90.97% to 100.00%), clinical specificity of 96.72% (95% CI, 88.65% to 99.60%), and overall accuracy of 98.00% (95% CI, 92.96% to 99.76%).
Conclusions
Taken together, these findings indicate that the RT-LAMP assay reported here solves important practical drawbacks to the deployment of molecular diagnostics in the field and can be used to improve testing capacity, particularly in low- and middle-income countries.
| Original language | English |
|---|---|
| Pages (from-to) | 810-815 |
| Number of pages | 6 |
| Journal | Clinical Microbiology and Infection |
| Volume | 30 |
| Issue number | 6 |
| Early online date | 7 Mar 2024 |
| DOIs | |
| Publication status | E-pub ahead of print - 7 Mar 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- CHIKV
- Diagnostic
- Mosquitoes
- Patients
- Point-of-care
- RT-LAMP
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