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Browsing by Author "Aguilera Flores, Marcela"

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    Strain-level identification of bacterial tomato pathogens directly from metagenomic sequences
    Mechan Llontop, Marco Enrique; Sharma, Parul; Aguilera Flores, Marcela; Yang, Shu; Pollock, Jill; Tian, Long; Huang, Chengjie; Rideout, Steven L.; Heath, Lenwood S.; Li, Song; Vinatzer, Boris A. (Scientific Societies, 2019-12-12)
    Routine strain-level identification of plant pathogens directly from symptomatic tissue could significantly improve plant disease control and prevention. Here we tested the Oxford Nanopore Technologies (ONT) MinIONTM sequencer for metagenomic sequencing of tomato plants either artificially inoculated with a known strain of the bacterial speck pathogen Pseudomonas syringae pv. tomato (Pto), or collected in the field and showing bacterial spot symptoms caused by either one of four Xanthomonas species. After species-level identification using ONT's WIMP software and the third party tools Sourmash and MetaMaps, we used Sourmash and MetaMaps with a custom database of representative genomes of bacterial tomato pathogens to attempt strain-level identification. In parallel, each metagenome was assembled and the longest contigs were used as query with the genome-based microbial identification Web service LINbase. Both the read-based and assembly-based approaches correctly identified Pto strain T1 in the artificially inoculated samples. The pathogen strain in most field samples was identified as a member of Xanthomonas perforans group 2. This result was confirmed by whole genome sequencing of colonies isolated from one of the samples. Although in our case, metagenome-based pathogen identification at the strain-level was achieved, caution still needs to be exerted when interpreting strain-level results because of the challenges inherent to assigning reads to specific strains and the error rate of nanopore sequencing.
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    Strain-level identification of tomato pathogens from metagenomic sequences obtained with the ONT MinION
    Sharma, Parul; Mechan Llontop, Marco E.; Aguilera Flores, Marcela; Li, Song; Vinatzer, Boris A. (Virginia Tech, 2020-03-25)
    Early detection and correct diagnosis of plant diseases is an essential component of sustainable production of food and other plant-derived products. Although molecular technologies are available, many of them are either slow because they depend on culturing the pathogen first, are limited to specific pathogen species and thus cannot detect any newly emerging diseases, or have low resolution. With recent advances in sequencing technologies, it has become possible to sequence the DNA of an entire plant sample, called the metagenome, at relatively low cost and with relatively easy and fast protocols using the Oxford Nanopore Technologies (ONT) MinIONTM device. MinIONTM software What’s in my pot (WIMP) offers read-based taxonomic identification from the metagenome. In this study, we have used the MinIONTM device to sequence laboratory-inoculated tomato plants and field samples of infected tomato plants to establish the efficiency of WIMP in identifying the underlying plant pathogens. The taxonomic classifications, at the species-level, from WIMP were compared with the results from the third party Sourmash and MetaMaps tools. Since species-level identification is not always sufficient, for example, when tracking pathogen dissemination pathways, custom reference libraries were used to attempt strain-level classification with Sourmash and MetaMaps as well as identification with the LINbase Web service based on metagenome-assembled genomes (MAGs). Our study showed that reliable species-level identification is possible with either WIMP, Sourmash, or MetaMaps. There is the potential for strain-level accuracy, however improvements in the error rate of the MinIONTM and availability of appropriate reference databases is necessary.