title: Improved taxonomic assignment of human intestinal 16S rRNA sequences by a dedicated reference database.
abstract: BACKGROUND
  Current sequencing technology enables taxonomic profiling of microbial ecosystems at high resolution and depth by using the 16S rRNA gene as a phylogenetic marker. Taxonomic assignation of newly acquired data is based on sequence comparisons with comprehensive reference databases to find consensus taxonomy for representative sequences. Nevertheless, even with well-characterised ecosystems like the human intestinal microbiota it is challenging to assign genus and species level taxonomy to 16S rRNA amplicon reads. A part of the explanation may lie in the sheer size of the search space where competition from a multitude of highly similar sequences may not allow reliable assignation at low taxonomic levels. However, when studying a particular environment such as the human intestine, it can be argued that a reference database comprising only sequences that are native to the environment would be sufficient, effectively reducing the search space.
  
  
  RESULTS
  We constructed a 16S rRNA gene database based on high-quality sequences specific for human intestinal microbiota, resulting in curated data set consisting of 2473 unique prokaryotic species-like groups and their taxonomic lineages, and compared its performance against the Greengenes and Silva databases. The results showed that regardless of used assignment algorithm, our database improved taxonomic assignation of 16S rRNA sequencing data by enabling significantly higher species and genus level assignation rate while preserving taxonomic diversity and demanding less computational resources.
  
  
  CONCLUSIONS
  The curated human intestinal 16S rRNA gene taxonomic database of about 2500 species-like groups described here provides a practical solution for significantly improved taxonomic assignment for phylogenetic studies of the human intestinal microbiota.
authors.affiliation: Department of Veterinary Biosciences, University of Helsinki, Helsinki, Finland. jarmo.ritari@gmail.com.
authors.forename: Jarmo
authors.initials: J
authors.lastname: Ritari
authors.affiliation: Department of Veterinary Biosciences, University of Helsinki, Helsinki, Finland. jarkko.salojarvi@helsinki.fi.
authors.forename: Jarkko
authors.initials: J
authors.lastname: Salojärvi
authors.affiliation: Department of Veterinary Biosciences, University of Helsinki, Helsinki, Finland. leo.lahti@iki.fi.|Laboratory of Microbiology, Wageningen University, Wageningen, the Netherlands. leo.lahti@iki.fi.
authors.forename: Leo
authors.initials: L
authors.lastname: Lahti
authors.affiliation: Department of Veterinary Biosciences, University of Helsinki, Helsinki, Finland. willem.devos@wur.nl.|Laboratory of Microbiology, Wageningen University, Wageningen, the Netherlands. willem.devos@wur.nl.|Department of Bacteriology and Immunology, University of Helsinki, Helsinki, Finland. willem.devos@wur.nl.
authors.forename: Willem M
authors.initials: WM
authors.lastname: de Vos
mesh_terms: D000465:Algorithms; D001419:Bacteria / Q000145:classification* / Q000235:genetics; D019295:Computational Biology / Q000379:methods; D066289:Data Curation; D030541:Databases, Genetic; D000069196:Gastrointestinal Microbiome; D006801:Humans; D010802:Phylogeny; D012329:RNA, Bacterial / Q000032:analysis; D012336:RNA, Ribosomal, 16S / Q000032:analysis*; D017423:Sequence Analysis, RNA
chemical_list: D012329:RNA, Bacterial; D012336:RNA, Ribosomal, 16S