Strain-Level Identification of Bacterial Tomato Pathogens Directly from Metagenomic Sequences
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...
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Veröffentlicht in: | Phytopathology 2020-04, Vol.110 (4), p.768-779 |
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creator | Mechan Llontop, Marco E Sharma, Parul Aguilera Flores, Marcela Yang, Shu Pollok, Jill Tian, Long Huang, Chenjie Rideout, Steve Heath, Lenwood S Li, Song Vinatzer, Boris A |
description | 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
pv.
or collected in the field and showing bacterial spot symptoms caused by one of four
species. After species-level identification via 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
pv.
strain T1 in the artificially inoculated samples. The pathogen strain in most field samples was identified as a member of
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 must be exercised in interpreting strain-level results because of the challenges inherent to assigning reads to specific strains and the error rate of nanopore sequencing. |
doi_str_mv | 10.1094/PHYTO-09-19-0351-R |
format | Article |
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pv.
or collected in the field and showing bacterial spot symptoms caused by one of four
species. After species-level identification via 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
pv.
strain T1 in the artificially inoculated samples. The pathogen strain in most field samples was identified as a member of
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 must be exercised in interpreting strain-level results because of the challenges inherent to assigning reads to specific strains and the error rate of nanopore sequencing.</description><identifier>ISSN: 0031-949X</identifier><identifier>EISSN: 1943-7684</identifier><identifier>DOI: 10.1094/PHYTO-09-19-0351-R</identifier><identifier>PMID: 31829116</identifier><language>eng</language><publisher>United States</publisher><subject>Bacteria ; Lycopersicon esculentum ; Metagenome ; Plant Diseases ; Xanthomonas</subject><ispartof>Phytopathology, 2020-04, Vol.110 (4), p.768-779</ispartof><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c347t-47938732c6e0ac4ca2a99e89cdaf591129cb6b48ba05827b7e59d1eeeac7acc03</citedby><cites>FETCH-LOGICAL-c347t-47938732c6e0ac4ca2a99e89cdaf591129cb6b48ba05827b7e59d1eeeac7acc03</cites><orcidid>0000-0001-5644-4768</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,3724,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31829116$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Mechan Llontop, Marco E</creatorcontrib><creatorcontrib>Sharma, Parul</creatorcontrib><creatorcontrib>Aguilera Flores, Marcela</creatorcontrib><creatorcontrib>Yang, Shu</creatorcontrib><creatorcontrib>Pollok, Jill</creatorcontrib><creatorcontrib>Tian, Long</creatorcontrib><creatorcontrib>Huang, Chenjie</creatorcontrib><creatorcontrib>Rideout, Steve</creatorcontrib><creatorcontrib>Heath, Lenwood S</creatorcontrib><creatorcontrib>Li, Song</creatorcontrib><creatorcontrib>Vinatzer, Boris A</creatorcontrib><title>Strain-Level Identification of Bacterial Tomato Pathogens Directly from Metagenomic Sequences</title><title>Phytopathology</title><addtitle>Phytopathology</addtitle><description>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
pv.
or collected in the field and showing bacterial spot symptoms caused by one of four
species. After species-level identification via 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
pv.
strain T1 in the artificially inoculated samples. The pathogen strain in most field samples was identified as a member of
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 must be exercised in interpreting strain-level results because of the challenges inherent to assigning reads to specific strains and the error rate of nanopore sequencing.</description><subject>Bacteria</subject><subject>Lycopersicon esculentum</subject><subject>Metagenome</subject><subject>Plant Diseases</subject><subject>Xanthomonas</subject><issn>0031-949X</issn><issn>1943-7684</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNo9kEtPHDEQhC0EguXxB3JAPnIx8WNmPH1MSAJIG4FgI4VDZPV4e4ijmTGxvZH49wzhcSqpVVVd-hj7oOSpklB9vL64W10JCUKBkKZW4maLLRRURtimrbbZQkqjBFTwc4_t5_xHSmnbutlle0a1GpRqFuzXbUkYJrGkfzTwyzVNJfTBYwlx4rHnn9EXSgEHvoojlsivsfyO9zRl_iUk8mV45H2KI_9OBedzHIPnt_R3Q5OnfMh2ehwyHb3qAfvx7evq7EIsr84vzz4thTeVLaKyYFprtG9Ioq88agSgFvwa-3reqcF3TVe1Hcq61bazVMNaERF6i95Lc8BOXnofUpxf5-LGkD0NA04UN9lpo2sNFhTMVv1i9SnmnKh3DymMmB6dku4Zq_uP1UlwCtwzVnczh45f-zfdSOv3yBtH8wRD8XWm</recordid><startdate>20200401</startdate><enddate>20200401</enddate><creator>Mechan Llontop, Marco E</creator><creator>Sharma, Parul</creator><creator>Aguilera Flores, Marcela</creator><creator>Yang, Shu</creator><creator>Pollok, Jill</creator><creator>Tian, Long</creator><creator>Huang, Chenjie</creator><creator>Rideout, Steve</creator><creator>Heath, Lenwood S</creator><creator>Li, Song</creator><creator>Vinatzer, Boris A</creator><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-5644-4768</orcidid></search><sort><creationdate>20200401</creationdate><title>Strain-Level Identification of Bacterial Tomato Pathogens Directly from Metagenomic Sequences</title><author>Mechan Llontop, Marco E ; Sharma, Parul ; Aguilera Flores, Marcela ; Yang, Shu ; Pollok, Jill ; Tian, Long ; Huang, Chenjie ; Rideout, Steve ; Heath, Lenwood S ; Li, Song ; Vinatzer, Boris A</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c347t-47938732c6e0ac4ca2a99e89cdaf591129cb6b48ba05827b7e59d1eeeac7acc03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Bacteria</topic><topic>Lycopersicon esculentum</topic><topic>Metagenome</topic><topic>Plant Diseases</topic><topic>Xanthomonas</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mechan Llontop, Marco E</creatorcontrib><creatorcontrib>Sharma, Parul</creatorcontrib><creatorcontrib>Aguilera Flores, Marcela</creatorcontrib><creatorcontrib>Yang, Shu</creatorcontrib><creatorcontrib>Pollok, Jill</creatorcontrib><creatorcontrib>Tian, Long</creatorcontrib><creatorcontrib>Huang, Chenjie</creatorcontrib><creatorcontrib>Rideout, Steve</creatorcontrib><creatorcontrib>Heath, Lenwood S</creatorcontrib><creatorcontrib>Li, Song</creatorcontrib><creatorcontrib>Vinatzer, Boris A</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Phytopathology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mechan Llontop, Marco E</au><au>Sharma, Parul</au><au>Aguilera Flores, Marcela</au><au>Yang, Shu</au><au>Pollok, Jill</au><au>Tian, Long</au><au>Huang, Chenjie</au><au>Rideout, Steve</au><au>Heath, Lenwood S</au><au>Li, Song</au><au>Vinatzer, Boris A</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Strain-Level Identification of Bacterial Tomato Pathogens Directly from Metagenomic Sequences</atitle><jtitle>Phytopathology</jtitle><addtitle>Phytopathology</addtitle><date>2020-04-01</date><risdate>2020</risdate><volume>110</volume><issue>4</issue><spage>768</spage><epage>779</epage><pages>768-779</pages><issn>0031-949X</issn><eissn>1943-7684</eissn><abstract>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
pv.
or collected in the field and showing bacterial spot symptoms caused by one of four
species. After species-level identification via 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
pv.
strain T1 in the artificially inoculated samples. The pathogen strain in most field samples was identified as a member of
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 must be exercised in interpreting strain-level results because of the challenges inherent to assigning reads to specific strains and the error rate of nanopore sequencing.</abstract><cop>United States</cop><pmid>31829116</pmid><doi>10.1094/PHYTO-09-19-0351-R</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0001-5644-4768</orcidid><oa>free_for_read</oa></addata></record> |
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source | MEDLINE; EZB-FREE-00999 freely available EZB journals; Alma/SFX Local Collection; American Phytopathological Society Journal Back Issues |
subjects | Bacteria Lycopersicon esculentum Metagenome Plant Diseases Xanthomonas |
title | Strain-Level Identification of Bacterial Tomato Pathogens Directly from Metagenomic Sequences |
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