RESUMO
Tristeza is a highly destructive disease of citrus caused by the phloem-limited, flexuous filamentous Citrus tristeza virus (CTV) in the genus Closterovirus and the family Closteroviridae. It has been a major constraint for higher productivity and has destroyed millions of citrus trees globally. CTV is graft transmissible and spread through use of virus infected nursery plants. Therefore, virus detection by using specific and reliable diagnostic tools is very important to mitigate disease outbreaks. Currently, the standard molecular techniques for CTV detection include RT-PCR and RT-qPCR. These diagnostic methods are highly sensitive but time consuming, labor intensive and require sophisticated expensive instruments, thus not suitable for point-of-care use. In the present study, we report the development of a rapid, sensitive, robust, reliable, and highly specific reverse transcription-RPA technique coupled with a lateral flow immunochromatographic assay (CTV-RT-RPA-LFICA). RT-RPA technique was standardized to amplify the coat protein gene of CTV (CTV-p25) and detect double labeled amplicons on a sandwich immunoassay by designing specific labeled primer pair and probe combinations. The optimally performing primer set (CTRPA-F1/CTRPA-R9-Btn) and the corresponding TwistAmp nfo probe (CTRPA-Probe) was optimized for temperature and reaction time using purified cDNA and viral RNA as template. The sensitivity of the developed assay was compared with other detection techniques using in vitro-transcribed RNA. The efficacy and specificity of the assay was evaluated using CTV positive controls, healthy samples, field grown citrus plants of unknown status, and other virus and bacterial pathogens that infect citrus plants. The RT-RPA-LFICA was able to detect ≤ 141 fg of RNA when cDNA used as a template. The assay detected ≤ 0.23 ng/µl of CTV RNA when directly used as template without cross-reactivity with other citrus pathogens. Best results were achieved at the isothermal temperature of 40 °C within 15-20 min. The study demonstrated that RT-RPA-LFICA has potential to become an improved detection technique for end users in bud-wood certification and quarantine programs and a promising platform for rapid point-of-care diagnostics for citrus farmers and small nurseries in low resource settings.
