Carvajal-Rojas, Sofía

Publications (1)

Real-time on-site detection of the three ‘Candidatus Liberibacter’ species associated with HLB disease: a rapid and validated method

Morán et al. (2023). Frontiers in Plant Science 14
Names (1)
Plant Science
Huanglongbing (HLB) is a devastating disease that affects all commercial citrus species worldwide. The disease is associated with bacteria of three species of the genus ‘Candidatus Liberibacter’ transmitted by psyllid vectors. To date, HLB has no cure, so preventing its introduction into HLB-free areas is the best strategy to control its spread. For that, the use of accurate, sensitive, specific, and reliable detection methods is critical for good integrated management of this serious disease. This study presents a new real-time recombinase polymerase amplification (RPA) protocol able to detect the three ‘Ca. Liberibacter’ species associated with HLB in both plant and insect samples, validated according to European and Mediterranean Plant Protection Organization (EPPO) guidelines and tested on 365 samples from nine different geographic origins. This new protocol does not require nucleic acid purification or specialized equipment, making it ideal to be used under field conditions. It is based on specific primers and probe targeting a region of fusA gene, which shows a specificity of 94%–100%, both in silico and in vitro, for the ‘Ca. Liberibacter’ species associated with HLB. The analytical sensitivity of the new protocol is excellent, with a reliable detection limit in the order of 101 copies per microliter in HLB-infected plant and insect material. The repeatability and reproducibility of the new methods showed consistent results. Diagnostic parameters of the new RPA protocol were calculated and compared with the gold standard technique, a quantitative real-time PCR, in both crude extracts of citrus plants and insect vectors. The agreement between the two techniques was almost perfect according to the estimated Cohen’s kappa index, with a diagnostic sensitivity and specificity of 83.89% and 100%, respectively, and a relative accuracy of 91.59%. Moreover, the results are obtained in less than 35 min. All these results indicate the potential of this new RPA protocol to be implemented as a reliable on-site detection kit for HLB due to its simplicity, speed, and portability.