4.6 Article

Development of a duplex droplet digital PCR assay for absolute quantitative detection of Candidatus Liberibacter asiaticus

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PLOS ONE
卷 13, 期 5, 页码 -

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PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0197184

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  1. California Citrus Research Board [YOK-17 (ARS 58-2034-7-018)]
  2. Citrus Research Board [5300-17AA (ARS17-5300-191)]

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Huanglongbing (HLB, citrus greening) is a devastating citrus disease affecting citrus production worldwide. It is associated with the bacterium Candidatus Liberibacter asiaticus (CLas) and is vectored by the Asian citrus psyllid (ACP). Currently, diagnosis of CLas in regulatory samples is based on real-time quantitative polymerase chain reaction (qPCR) using 16S rRNA gene specific primers/probe. The detection of CLas using qPCR is challenging due to low pathogen titer and uneven distribution in infected plants and exacerbated by sampling issues and presence of inhibitors. This study evaluated a duplex droplet digital polymerase chain reaction (ddPCR) using multi-copy gene targets, 16S and RNR, to simultaneously detect CLas DNA targets in the same sample for unambiguous detection of the HLB pathogen in DNA extracts from citrus leaves and ACP. Standard curve analyses on tenfold dilution series with plasmid, citrus leaf and ACP DNA showed that both ddPCR and qPCR exhibited good linearity and efficiency in the duplex assay. CLas-infected low titer samples were used to validate the duplex ddPCR and qPCR performance and demonstrated that detection rate is higher when both 16S and RNR primers were used in duplex assay. However, the receiver operating characteristic analysis indicated that area under the curve for RNR primer was significantly broader, compared to 16S primers for CLas detection at low target titer. The absolute quantification of CLas at variable titers was reproducible and repeatable for both primer sets and the ddPCR showed higher resilience to PCR inhibitors with citrus leaf and ACP extracts. Hence, the resultant duplex ddPCR assay resulted in a significantly improved detection platform for diagnosis of CLas in samples with low pathogen titer.

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