Multiplex real-time PCR for detection and quantification of Colletotrichum abscissum and C. gloeosporioides on Citrus leaves
2019
Pereira, W. V. | Bertolini, Edson | Cambra, Mariano | Massola Junior, N. S.
Colletotrichum abscissum and C. gloeosporioides are the causal agents of citrus Postbloom Fruit Drop (PFD), a major disease in several countries of the American continent. These pathogens infect only floral structures; however, in the absence of floral tissue, they survive asymptomatically on the leaf tissue. Thus, detecting and quantifying pathogens on leaves are critical for epidemiological studies. Colletotrichum species are detected through isolation, serological methods and conventional PCR, but these techniques are not effective for accurate detection of PFD agents. This study aimed to develop specific, more sensitive, faster and less laborious techniques than the traditional ones routinely used. We developed, standardized and validated a multiplex real-time PCR with high sensitivity (98–99.3%) and specificity (94.3–97.1%) for the detection and quantification of both pathogens. This technique was 1000 and 10,000 times more sensitive than Nested-PCR and PCR, respectively for the detection of C. abscissum. Similarly, the multiplex qPCR was 100 and 1000 times more sensitive than Nested-PCR and PCR, respectively for the detection of C. gloeosporioides. The diagnostic parameters used to validate the multiplex qPCR showed a high positive (17–35) and low negative (0.006–0.95) likelihood ratios, low percentage of false positives (2.8–5.6%) and false negatives (0.6–1.9%), good agreement between the results generated between qPCR and multiplex qPCR, revealed by the Kappa index (0.91–0.98) and coincidental results (95–99%). All parameters indicated that the multiplex qPCR was effectively validated to detect and quantify the causal agents of PFD.
Afficher plus [+] Moins [-]Mots clés AGROVOC
Informations bibliographiques
Cette notice bibliographique a été fournie par Institut Valencià d'Investigacions Agràries
Découvrez la collection de ce fournisseur de données dans AGRIS