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AutoMLST: an automated web server for generating multi-locus species trees highlighting natural product potential.
Alanjary, Mohammad; Steinke, Katharina; Ziemert, Nadine.
Affiliation
  • Alanjary M; Interfaculty Institute of Microbiology and Infection Medicine Tübingen, University of Tübingen, Tübingen, Germany.
  • Steinke K; German Centre for Infection Research (DZIF), Partner Site Tübingen, Tübingen, Germany.
  • Ziemert N; Interfaculty Institute of Microbiology and Infection Medicine Tübingen, University of Tübingen, Tübingen, Germany.
Nucleic Acids Res ; 47(W1): W276-W282, 2019 07 02.
Article in En | MEDLINE | ID: mdl-30997504
ABSTRACT
Understanding the evolutionary background of a bacterial isolate has applications for a wide range of research. However generating an accurate species phylogeny remains challenging. Reliance on 16S rDNA for species identification currently remains popular. Unfortunately, this widespread method suffers from low resolution at the species level due to high sequence conservation. Currently, there is now a wealth of genomic data that can be used to yield more accurate species designations via modern phylogenetic methods and multiple genetic loci. However, these often require extensive expertise and time. The Automated Multi-Locus Species Tree (autoMLST) was thus developed to provide a rapid 'one-click' pipeline to simplify this workflow at https//automlst.ziemertlab.com. This server utilizes Multi-Locus Sequence Analysis (MLSA) to produce high-resolution species trees; this does not preform multi-locus sequence typing (MLST), a related classification method. The resulting phylogenetic tree also includes helpful annotations, such as species clade designations and secondary metabolite counts to aid natural product prospecting. Distinct from currently available web-interfaces, autoMLST can automate selection of reference genomes and out-group organisms based on one or more query genomes. This enables a wide range of researchers to perform rigorous phylogenetic analyses more rapidly compared to manual MLSA workflows.
Subject(s)

Full text: 1 Database: MEDLINE Main subject: Phylogeny / Bacteria / Software / Internet / Genomics / Multilocus Sequence Typing Language: En Year: 2019 Type: Article

Full text: 1 Database: MEDLINE Main subject: Phylogeny / Bacteria / Software / Internet / Genomics / Multilocus Sequence Typing Language: En Year: 2019 Type: Article