Transboundary and Emerging Diseases · 2015 · 64 citations · 23 references
MedicineInfectious DiseasesMicrobiologyMolecular DiagnosticsMolecular VirologyVirologyInfectious Disease Molecular TestingNucleic Acid Amplification TestingPathogen DetectionRapid Diagnostic TestsViral DiagnosticsAnalytical SensitivityDiagnostic Assay DevelopmentLoop-mediated Isothermal Amplification (Lamp)Molecular Detection AssaysRapid Detection AssaysRapid Viral DiagnosticsReal-time Detection AssaysVirus Detection Assays
Accurate, timely diagnosis is essential for the control, monitoring and eradication of foot-and-mouth disease (FMD). Clinical samples from suspect cases are normally tested at reference laboratories. However, transport of samples to these centralized facilities can be a lengthy process that can impose delays on critical decision making. These concerns have motivated work to evaluate simple-to-use technologies, including molecular-based diagnostic platforms, that can be deployed closer to suspect cases of FMD. In this context, FMD virus (FMDV)-specific reverse transcription loop-mediated isothermal amplification (RT-LAMP) and real-time RT-PCR (rRT-PCR) assays, compatible with simple sample preparation methods and in situ visualization, have been developed which share equivalent analytical sensitivity with laboratory-based rRT-PCR. However, the lack of robust 'ready-to-use kits' that utilize stabilized reagents limits the deployment of these tests into field settings. To address this gap, this study describes the performance of lyophilized rRT-PCR and RT-LAMP assays to detect FMDV. Both of these assays are compatible with the use of fluorescence to monitor amplification in real-time, and for the RT-LAMP assays end point detection could also be achieved using molecular lateral flow devices. Lyophilization of reagents did not adversely affect the performance of the assays. Importantly, when these assays were deployed into challenging laboratory and field settings within East Africa they proved to be reliable in their ability to detect FMDV in a range of clinical samples from acutely infected as well as convalescent cattle. These data support the use of highly sensitive molecular assays into field settings for simple and rapid detection of FMDV.
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R: A Language and Environment for Statistical Computing
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Natural Sciences, Computer Science, Statistical Computing +10
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