Abstract

Microbial taxonomy is increasingly influenced by genome-based computational methods. Yet such analyses can be complex and require expert knowledge. Here we introduce TYGS, the Type (Strain) Genome Server, a user-friendly high-throughput web server for genome-based prokaryote taxonomy, connected to a large, continuously growing database of genomic, taxonomic and nomenclatural information. It infers genome-scale phylogenies and state-of-the-art estimates for species and subspecies boundaries from user-defined and automatically determined closest type genome sequences. TYGS also provides comprehensive access to nomenclature, synonymy and associated taxonomic literature. Clinically important examples demonstrate how TYGS can yield new insights into microbial classification, such as evidence for a species-level separation of previously proposed subspecies of Salmonella enterica. TYGS is an integrated approach for the classification of microbes that unlocks novel scientific approaches to microbiologists worldwide and is particularly helpful for the rapidly expanding field of genome-based taxonomic descriptions of new genera, species or subspecies. Information on type material is of fundamental importance in prokaryote taxonomy. Here, the authors develop TYGS, the Type (Strain) Genome Server, for genome-based prokaryote taxonomy and analysis using a comprehensive database of genomic and taxonomic data.

Keywords

SubspeciesGenomeTaxonomy (biology)ProkaryoteBiologyGenomicsComputational biologyComputer scienceEvolutionary biologyEcologyGeneticsGene

MeSH Terms

ArchaeaBacteriaDatabasesGeneticGenomeArchaealGenomeBacterialGenomicsPhylogeny

Affiliated Institutions

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Publication Info

Year
2019
Type
article
Volume
10
Issue
1
Pages
2182-2182
Citations
2772
Access
Closed

Social Impact

Social media, news, blog, policy document mentions

Citation Metrics

2772
OpenAlex
188
Influential

Cite This

Jan P. Meier‐Kolthoff, Markus Göker (2019). TYGS is an automated high-throughput platform for state-of-the-art genome-based taxonomy. Nature Communications , 10 (1) , 2182-2182. https://doi.org/10.1038/s41467-019-10210-3

Identifiers

DOI
10.1038/s41467-019-10210-3
PMID
31097708
PMCID
PMC6522516

Data Quality

Data completeness: 90%