RT Journal Article
SR Electronic
T1 Strain-level identification of bacterial tomato pathogens directly from metagenomic sequences
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 777706
DO 10.1101/777706
A1 Marco E. Mechan Llontop
A1 Parul Sharma
A1 Marcela Aguilera Flores
A1 Shu Yang
A1 Jill Pollock
A1 Long Tian
A1 Chenjie Huang
A1 Steve Rideout
A1 Lenwood S. Heath
A1 Song Li
A1 Boris A. Vinatzer
YR 2019
UL http://biorxiv.org/content/early/2019/09/23/777706.abstract
AB 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) MinION™ 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.