Investigating plant disease outbreaks with long-read metagenomics: sensitive detection and highly resolved phylogenetic reconstruction applied to Xylella fastidiosa

Johnson, Marcela A; Liu, Haijie; Bush, Elizabeth; Sharma, Parul; Yang, Shu; Mazloom, Reza; Heath, Lenwood S.; Nita, Mizuho; Li, Song; Vinatzer, Boris A.

doi:10.1099/mgen.0.000822

Cited by 9 publications

(8 citation statements)

References 52 publications

(113 reference statements)

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“…The MinION is a promising fast-detection technology for plant pathogen detection [137][138][139] because the instrument is smaller than a smartphone and provides output data within a few minutes. It has been explored for the sequencing of bacterial and virus pathogens, 132 viruses 103 ; identifying Xylella fastidiosa subspecies and sequence in naturally infected olive samples 140 and in grapevine 141 and for the detection Fusarium oxysporum on Zinnia hybrida (zinnia) plants. 142…”

Section: Nanopore Sequencing Technologymentioning

confidence: 99%

Next‐generation methods for early disease detection in crops

Trippa,

Scalenghe,

Basso

et al. 2023

Pest Management Science

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BackgroundPlant pathogens are commonly identified in the field by the typical disease symptoms that they can cause. The efficient early detection and identification of pathogens are essential procedures to adopt effective management practices that reduce or prevent their spread in order to mitigate the negative impacts of the disease. Herein, in this review were presented and discussed the traditional and innovative methods for early detection of the plant pathogens highlighting their major advantages and limitations.Resultstraditional techniques of diagnosis used for plant pathogen identification are focused typically on the DNA, RNA (when molecular methods), and proteins or peptides (when serological methods) of the pathogens. Serological methods based on mainly enzyme‐linked immunosorbent assay (ELISA) are the most common method used for pathogen detection due to their high‐throughput potential and low cost. This technique is not particularly reliable and sufficiently sensitive for many pathogens detection during the asymptomatic stage of infection. For non‐cultivable pathogens in the laboratory, nucleic acid‐based technology is the best choice for consistent pathogen detection or identification. Lateral flow systems are innovative tools that allow fast and accurate results even in the field conditions, but they have sensitivity issues to be overcome. PCR assays performed on last‐generation portable thermocyclers may provide rapid detection results in situ.ConclusionThe advent of portable instruments can speed pathogen detection, reduce commercial costs, and potentially can revolutionize plant pathology. This review provides information on current methodologies and procedures for the effective detection of different plant pathogens.This article is protected by copyright. All rights reserved.

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Section: Nanopore Sequencing Technologymentioning

confidence: 99%

Next‐generation methods for early disease detection in crops

Trippa,

Scalenghe,

Basso

et al. 2023

Pest Management Science

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show abstract

“…Moreover, nanopore sequencing using the handheld MinION sequencer has seen renewed interest in disease detection using metagenomics or RNA-seq, and it has been successfully used to detect fungi and bacteria, sometimes with identification down to the strain level [30][31][32][33][34]. In addition, (meta)genomics is being progressively adopted for the efficient tracing of the origin(s) of outbreaks or for high resolution phylogeographic studies of pathogens, such as Xylella fastidiosa [35] or Fusarium graminearum [36].…”

Section: Discussionmentioning

confidence: 99%

“…Since each participant independently performed the mapping, data processing steps differed slightly between them (File S1). Most datasets underwent some basic preprocessing in the form of quality filtering (99) and/or adapter removal (92), in some cases followed by merging of forward and reverse reads (35) and/or duplicate removal (12). Of the 101 datasets, 79 were mapped using BWA, 18 using Geneious, and 4 using CLC Genomics Workbench.…”

Section: Rrna Depletion During Library Prep Reduced the Amount Of Pla...mentioning

confidence: 99%

Looking beyond Virus Detection in RNA Sequencing Data: Lessons Learned from a Community-Based Effort to Detect Cellular Plant Pathogens and Pests

Haegeman,

Foucart,

De Jonghe

et al. 2023

Plants

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High-throughput sequencing (HTS), more specifically RNA sequencing of plant tissues, has become an indispensable tool for plant virologists to detect and identify plant viruses. During the data analysis step, plant virologists typically compare the obtained sequences to reference virus databases. In this way, they are neglecting sequences without homologies to viruses, which usually represent the majority of sequencing reads. We hypothesized that traces of other pathogens might be detected in this unused sequence data. In the present study, our goal was to investigate whether total RNA-seq data, as generated for plant virus detection, is also suitable for the detection of other plant pathogens and pests. As proof of concept, we first analyzed RNA-seq datasets of plant materials with confirmed infections by cellular pathogens in order to check whether these non-viral pathogens could be easily detected in the data. Next, we set up a community effort to re-analyze existing Illumina RNA-seq datasets used for virus detection to check for the potential presence of non-viral pathogens or pests. In total, 101 datasets from 15 participants derived from 51 different plant species were re-analyzed, of which 37 were selected for subsequent in-depth analyses. In 29 of the 37 selected samples (78%), we found convincing traces of non-viral plant pathogens or pests. The organisms most frequently detected in this way were fungi (15/37 datasets), followed by insects (13/37) and mites (9/37). The presence of some of the detected pathogens was confirmed by independent (q)PCRs analyses. After communicating the results, 6 out of the 15 participants indicated that they were unaware of the possible presence of these pathogens in their sample(s). All participants indicated that they would broaden the scope of their bioinformatic analyses in future studies and thus check for the presence of non-viral pathogens. In conclusion, we show that it is possible to detect non-viral pathogens or pests from total RNA-seq datasets, in this case primarily fungi, insects, and mites. With this study, we hope to raise awareness among plant virologists that their data might be useful for fellow plant pathologists in other disciplines (mycology, entomology, bacteriology) as well.

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“…High throughput Next Generation Sequencing (NGS) technologies allow sequencing of total DNA in samples, potentially pro-viding detection of X. fastidiosa and characterization to subspecies and strain levels, without requirement for pathogen cultivation. NGS based on Illumina (Bonants et al, 2019;Román-Reyna et al, 2022) or Oxford Nanopore technologies (Johnson et al, 2022) have been explored for fast detection and identification of X. fastidiosa. The potential advantages and disadvantages of both of these technologies are beyond the scope of this review.…”

Section: Molecular Diagnostic Tests For Early Detection and Subspecie...mentioning

confidence: 99%

Recent research accomplishments on early detection of Xylella fastidiosa outbreaks in the Mediterranean Basin

Velasco-Amo

Civera²,

Zarco‐Tejada³

et al. 2023

Phytopathol. Mediterr.

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Xylella fastidiosa is a major transboundary plant pest, causing severe socioeconomic impacts. Development of preventive strategies and methods for surveillance, early detection, monitoring, and accurate diagnosis of X. fastidiosa and its vectors, are keys to preventing the effects of this plant pathogen, and assist timely eradication or optimisation of containment measures. This review focuses on approaches for early detection of X. fastidiosa in the Mediterranean Basin, including development of climatic suitability risk maps to determine areas of potential establishment, and epidemiological models to assist in outbreak management through optimized surveillance and targeted responses. The usefulness of airborne hyperspectral and thermal images from remote sensing to discriminate X. fastidiosa infections from other biotic- and abiotic-induced spectral signatures is also discussed. The most commonly used methods for identifying X. fastidiosa in infected plants and vectors, and the molecular approaches available to genetically characterize X. fastidiosa strains, are described. Each of these approaches has trade-offs, but stepwise or simultaneous combinations of these methods may help to contain X. fastidiosa epidemics in the Mediterranean Basin.

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Investigating plant disease outbreaks with long-read metagenomics: sensitive detection and highly resolved phylogenetic reconstruction applied to Xylella fastidiosa

Cited by 9 publications

References 52 publications

Next‐generation methods for early disease detection in crops

Next‐generation methods for early disease detection in crops

Looking beyond Virus Detection in RNA Sequencing Data: Lessons Learned from a Community-Based Effort to Detect Cellular Plant Pathogens and Pests

Recent research accomplishments on early detection of Xylella fastidiosa outbreaks in the Mediterranean Basin

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