Sie befinden Sich nicht im Netzwerk der Universität Paderborn. Der Zugriff auf elektronische Ressourcen ist gegebenenfalls nur via VPN oder Shibboleth (DFN-AAI) möglich. mehr Informationen...
Quantitative distribution of Citrus yellow mosaic badnavirus in sweet orange (Citrus sinensis) and its implication in developing disease diagnostics
Ist Teil von
Journal of virological methods, 2018-09, Vol.259, p.25-31
Ort / Verlag
Netherlands: Elsevier B.V
Erscheinungsjahr
2018
Link zum Volltext
Quelle
Alma/SFX Local Collection
Beschreibungen/Notizen
•Citrus yellow mosaic badnavirus (CMBV) is a quarantined pathogen that is geographically restricted to India.•To prevent unintentional movement of the virus to other major citrus-growing countries, a sensitive, validated diagnostic tool is needed.•Here, we developed a SYBR Green real-time PCR-based method to detect and quantify CMBV in different tissues of infected Mosambi sweet orange (Citrus sinensis), and compared its sensitivity to conventional PCR protocols.•The detection limit of CMBV by conventional PCR was 2.5 × 104 copies per 5 ng of total genomic DNA, while the detection limit of real-time PCR was found to be 4.6 × 102 virus copies per 5 ng of viral DNA.•The viral load varied between different tissues. The highest concentration occurred in feeder roots (3.5 × 108 copies per 5 ng of total genomic DNA) and the lowest in thorns (1 × 106 copies per 5 ng of total genomic DNA).•The variation in viral load within different tissues suggests movement of the virus within an infected plant that follows the path of photo-assimilates via the phloem.•In addition to information on virus movement, the distribution of CMBV in different tissues helps with the selection of tissues with relatively higher viral load to sample for early and sensitive diagnosis of the disease, which will be useful for better disease management.
Citrus yellow mosaic badnavirus (CMBV) is the etiologic agent of citrus yellow mosaic disease, which has caused serious economic losses to Indian citrus industry. CMBV is a quarantined pathogen that is geographically restricted to India. To prevent unintentional movement of the virus to other major citrus-growing countries in fruits, root stocks or grafted citrus plants and facilitate trade, a sensitive, validated diagnostic tool is needed. In the present study, we developed a SYBR Green real-time PCR-based method to detect and quantify CMBV in different tissues of infected Mosambi sweet orange (Citrus sinensis) and compared its sensitivity to conventional PCR protocols. Primers were designed to recognize a portion of the CMBV capsid protein gene. Conventional and real-time PCR were performed on several different tissues: shoot tips, leaves displaying typical CMBV symptoms, asymptomatic leaves, senescent leaves, thorns, green stems and feeder roots. The detection limit of CMBV by conventional PCR was 2.5 × 104 copies per 5 ng of total genomic DNA, while the detection limit of real-time PCR was found to be 4.6 × 102 virus copies per 5 ng of viral DNA. The viral load varied between different tissues. The highest concentration occurred in feeder roots (3.5 × 108 copies per 5 ng of total genomic DNA) and the lowest in thorns (1 × 106 copies per 5 ng of total genomic DNA). The variation in viral load within different tissues suggests movement of the virus within an infected plant that follows the path of photo-assimilates via the phloem. In symptomatic leaves, the CMBV concentration was highest in the lamella followed by midrib and petiole, suggesting that virus resides inside these sections of a leaf and side by side symptoms develop. On the other hand, in asymptomatic leaves, the petiole contained higher virus load than the lamella and midrib suggesting that the pathogen gets established from the stem through the phloem into petiole then infects the lamella and midrib. In addition to information on virus movement, the distribution of CMBV in different tissues helps with the selection of tissues with relatively higher viral load to sample for early and sensitive diagnosis of the disease, which will be useful for better management of the disease in endemic areas.