bioRxivPathology
Nanopore sequencing for the detection and the identification of Xylella fastidiosa subspecies and sequence types from naturally infected plant material
L. Faino, V. Scala, A. Albanese, V. Modesti, A. Grottoli, N. Pucci, A. L'Aurora, M. Reverberi, S. Loreti
Abstract
Xylella fastidiosa (Xf) is a polyphagous gram-negative bacterial plant pathogen that can infect more than 300 plant species. It is endemic in America while, in 2013, Xf subsp. pauca was for the first time reported in Europe on olive tree in the Southern Italy. The availability of fast and reliable diagnostic tools is indispensable for managing current and future outbreaks of Xf. In this work, we used the Oxford Nanopore Technologies (ONT) device MinION platform for detecting and identifying Xf at species, subspecies and Sequence Type (ST) level straight from infected plant material. The study showed the possibility to detect Xf by direct DNA sequencing and identify the subspecies in highly infected samples. In order to improve sensitivity, Nanopore amplicon sequencing was assessed. Using primers within the set of the seven MLST officially adopted for identifying Xf at type strain level, we developed a workflow consisting in a multiple PCR and an ad hoc pipeline to generate MLST consensus after Nanopore-sequencing of the amplicons. The here-developed combined approach achieved a sensitivity higher than real-time PCR allowing within few hours, the detection and identification of Xf at ST level in infected plant material, also at low level of contamination. Originality Significance StatementIn this work we developed a methodology that allows the detection and identification of Xylella fastidiosa in plant using the Nanopore technology portable device MinION. The approach that we develop resulted more sensitive than methods currently used for detecting X. fastidiosa, like real-time PCR. This approach can be extensively used for X. fastidiosa detection and it may pave the road for the detection of other tedious vascular pathogens.
- organism: plant (other)
- assay: long-read sequencing
- research focus: differential expression
- approach: deep learning
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