Full-length 16S rRNA gene sequencing combined with adequate database selection improves the description of Arctic marine prokaryotic communities

Abstract

BackgroundHigh-throughput sequencing of the full-length 16S rRNA gene has improved the taxonomic classification of prokaryotes found in natural environments. However, sequencing of shorter regions from the same gene, like the V4-V5 region, can provide more cost-effective high throughput. It is unclear which approach best describes prokaryotic communities from underexplored environments. In this study, we hypothesize that high-throughput full-length 16S rRNA gene sequencing combined with adequate taxonomic databases improves the taxonomic description of prokaryotic communities from underexplored environments in comparison with high-throughput sequencing of a short region of the 16S rRNA gene.ResultsTo test our hypothesis, we compared taxonomic profiles of seawater samples from the Arctic Ocean using: full-length and V4-V5 16S rRNA gene sequencing in combination with either the Genome Taxonomy Database (GTDB) or the Silva taxonomy database. Our results show that all combinations of sequencing strategies and taxonomic databases present similar results at higher taxonomic levels. However, at lower taxonomic levels, namely family, genus, and most notably species level, the full-length approach led to higher proportions of Amplicon Sequence Variants (ASVs) assigned to formally valid taxa. Hence, the best taxonomic description was obtained by the full-length and GTDB combination, which in some cases allowed for the identification of intraspecific diversity of ASVs.ConclusionsWe conclude that coupling high-throughput full-length 16S rRNA gene sequencing with GTDB improves the description of microbiome profiling at lower taxonomic ranks. The improvements reported here provide more context for scientists to discuss microbial community dynamics within a solid taxonomic framework in environments like the Arctic Ocean with still underrepresented microbiome sequences in public databases.