16S rRNA phylogeny and clustering is not a reliable proxy for genome-based taxonomy in Streptomyces

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Abstract

Although Streptomyces is one of the most extensively studied genera of bacteria, their taxonomy remains contested and is suspected to contain significant species-level misclassification. Resolving the classification of Streptomyces would benefit many areas of study and applied microbiology that rely heavily on having an accurate ground truth classification of similar and dissimilar organisms, including comparative genomics-based searches for novel antimicrobials in the fight against the ongoing antimicrobial resistance (AMR) crisis. To attempt a resolution, we investigate taxonomic conflicts between 16S rRNA and whole genome classifications using all available 48,981 full-length 16S rRNA Streptomyces sequences from the combined SILVA, Greengenes, Ribosomal Database Project (RDP) and NCBI (National Center for Biotechnology Information) databases, and 2,276 publicly available Streptomyces genome assemblies. We construct a 16S gene tree for 14,239 distinct Streptomyces 16S rRNA sequences, identifying three major lineages of Streptomyces, and find that existing taxonomic classifications are inconsistent with the tree topology. We also use these data to delineate 16S and whole genome landscapes for Streptomyces, finding that 16S and whole-genome classifications of Streptomyces strains are frequently in disagreement, and in particular that 16S zero-radius Operational Taxonomic Units (zOTUs) are often inconsistent with Average Nucleotide Identity (ANI)-based taxonomy. Our results strongly imply that 16S rRNA sequence data does not map to taxonomy sufficiently well to delineate Streptomyces species reliably, and we propose that alternative markers should instead be adopted by the community for classification and metabarcoding. As much of current Streptomyces taxonomy has been determined or supported by historical 16S sequence data and may in parts be in error, we also propose that reclassification of the genus by alternative approaches is required.
Original languageEnglish
Place of PublicationIthaca, NY
Pages1-31
Number of pages31
DOIs
Publication statusPublished - 15 Aug 2023

Keywords

  • Streptomyces
  • taxonomy
  • evolution
  • phylogeny
  • diagnostics
  • drug discovery
  • bioinformatics
  • computational biology

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