Generation of Comprehensive Ecosystem-Specific Reference Databases with Species-Level Resolution by High-Throughput Full-Length 16S rRNA Gene Sequencing and Automated Taxonomy Assignment (AutoTax)

ABSTRACT High-throughput 16S rRNA gene amplicon sequencing is an essential method for studying the diversity and dynamics of microbial communities. However, this method is presently hampered by the lack of high-identity reference sequences for many environmental microbes in the public 16S rRNA gene...

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Autores principales:	Morten Simonsen Dueholm, Kasper Skytte Andersen, Simon Jon McIlroy, Jannie Munk Kristensen, Erika Yashiro, Søren Michael Karst, Mads Albertsen, Per Halkjær Nielsen
Formato:	article
Lenguaje:	EN
Publicado:	American Society for Microbiology 2020
Materias:	16S RNA gene sequencing microbial communities microbial ecology taxonomy wastewater treatment Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/97839cfdc7064442bf889f2a3f10e3d7
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spelling	oai:doaj.org-article:97839cfdc7064442bf889f2a3f10e3d72021-11-15T16:19:09ZGeneration of Comprehensive Ecosystem-Specific Reference Databases with Species-Level Resolution by High-Throughput Full-Length 16S rRNA Gene Sequencing and Automated Taxonomy Assignment (AutoTax)10.1128/mBio.01557-202150-7511https://doaj.org/article/97839cfdc7064442bf889f2a3f10e3d72020-10-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mBio.01557-20https://doaj.org/toc/2150-7511ABSTRACT High-throughput 16S rRNA gene amplicon sequencing is an essential method for studying the diversity and dynamics of microbial communities. However, this method is presently hampered by the lack of high-identity reference sequences for many environmental microbes in the public 16S rRNA gene reference databases and by the absence of a systematic and comprehensive taxonomy for the uncultured majority. Here, we demonstrate how high-throughput synthetic long-read sequencing can be applied to create ecosystem-specific full-length 16S rRNA gene amplicon sequence variant (FL-ASV) resolved reference databases that include high-identity references (>98.7% identity) for nearly all abundant bacteria (>0.01% relative abundance) using Danish wastewater treatment systems and anaerobic digesters as an example. In addition, we introduce a novel sequence identity-based approach for automated taxonomy assignment (AutoTax) that provides a complete seven-rank taxonomy for all reference sequences, using the SILVA taxonomy as a backbone, with stable placeholder names for unclassified taxa. The FL-ASVs are perfectly suited for the evaluation of taxonomic resolution and bias associated with primers commonly used for amplicon sequencing, allowing researchers to choose those that are ideal for their ecosystem. Reference databases processed with AutoTax greatly improves the classification of short-read 16S rRNA ASVs at the genus- and species-level, compared with the commonly used universal reference databases. Importantly, the placeholder names provide a way to explore the unclassified environmental taxa at different taxonomic ranks, which in combination with in situ analyses can be used to uncover their ecological roles.Morten Simonsen DueholmKasper Skytte AndersenSimon Jon McIlroyJannie Munk KristensenErika YashiroSøren Michael KarstMads AlbertsenPer Halkjær NielsenAmerican Society for Microbiologyarticle16S RNAgene sequencingmicrobial communitiesmicrobial ecologytaxonomywastewater treatmentMicrobiologyQR1-502ENmBio, Vol 11, Iss 5 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	16S RNA gene sequencing microbial communities microbial ecology taxonomy wastewater treatment Microbiology QR1-502
spellingShingle	16S RNA gene sequencing microbial communities microbial ecology taxonomy wastewater treatment Microbiology QR1-502 Morten Simonsen Dueholm Kasper Skytte Andersen Simon Jon McIlroy Jannie Munk Kristensen Erika Yashiro Søren Michael Karst Mads Albertsen Per Halkjær Nielsen Generation of Comprehensive Ecosystem-Specific Reference Databases with Species-Level Resolution by High-Throughput Full-Length 16S rRNA Gene Sequencing and Automated Taxonomy Assignment (AutoTax)
description	ABSTRACT High-throughput 16S rRNA gene amplicon sequencing is an essential method for studying the diversity and dynamics of microbial communities. However, this method is presently hampered by the lack of high-identity reference sequences for many environmental microbes in the public 16S rRNA gene reference databases and by the absence of a systematic and comprehensive taxonomy for the uncultured majority. Here, we demonstrate how high-throughput synthetic long-read sequencing can be applied to create ecosystem-specific full-length 16S rRNA gene amplicon sequence variant (FL-ASV) resolved reference databases that include high-identity references (>98.7% identity) for nearly all abundant bacteria (>0.01% relative abundance) using Danish wastewater treatment systems and anaerobic digesters as an example. In addition, we introduce a novel sequence identity-based approach for automated taxonomy assignment (AutoTax) that provides a complete seven-rank taxonomy for all reference sequences, using the SILVA taxonomy as a backbone, with stable placeholder names for unclassified taxa. The FL-ASVs are perfectly suited for the evaluation of taxonomic resolution and bias associated with primers commonly used for amplicon sequencing, allowing researchers to choose those that are ideal for their ecosystem. Reference databases processed with AutoTax greatly improves the classification of short-read 16S rRNA ASVs at the genus- and species-level, compared with the commonly used universal reference databases. Importantly, the placeholder names provide a way to explore the unclassified environmental taxa at different taxonomic ranks, which in combination with in situ analyses can be used to uncover their ecological roles.
format	article
author	Morten Simonsen Dueholm Kasper Skytte Andersen Simon Jon McIlroy Jannie Munk Kristensen Erika Yashiro Søren Michael Karst Mads Albertsen Per Halkjær Nielsen
author_facet	Morten Simonsen Dueholm Kasper Skytte Andersen Simon Jon McIlroy Jannie Munk Kristensen Erika Yashiro Søren Michael Karst Mads Albertsen Per Halkjær Nielsen
author_sort	Morten Simonsen Dueholm
title	Generation of Comprehensive Ecosystem-Specific Reference Databases with Species-Level Resolution by High-Throughput Full-Length 16S rRNA Gene Sequencing and Automated Taxonomy Assignment (AutoTax)
title_short	Generation of Comprehensive Ecosystem-Specific Reference Databases with Species-Level Resolution by High-Throughput Full-Length 16S rRNA Gene Sequencing and Automated Taxonomy Assignment (AutoTax)
title_full	Generation of Comprehensive Ecosystem-Specific Reference Databases with Species-Level Resolution by High-Throughput Full-Length 16S rRNA Gene Sequencing and Automated Taxonomy Assignment (AutoTax)
title_fullStr	Generation of Comprehensive Ecosystem-Specific Reference Databases with Species-Level Resolution by High-Throughput Full-Length 16S rRNA Gene Sequencing and Automated Taxonomy Assignment (AutoTax)
title_full_unstemmed	Generation of Comprehensive Ecosystem-Specific Reference Databases with Species-Level Resolution by High-Throughput Full-Length 16S rRNA Gene Sequencing and Automated Taxonomy Assignment (AutoTax)
title_sort	generation of comprehensive ecosystem-specific reference databases with species-level resolution by high-throughput full-length 16s rrna gene sequencing and automated taxonomy assignment (autotax)
publisher	American Society for Microbiology
publishDate	2020
url	https://doaj.org/article/97839cfdc7064442bf889f2a3f10e3d7
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Generation of Comprehensive Ecosystem-Specific Reference Databases with Species-Level Resolution by High-Throughput Full-Length 16S rRNA Gene Sequencing and Automated Taxonomy Assignment (AutoTax)

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