Uniting the classification of cultured and uncultured bacteria and archaea using 16S rRNA gene sequences

Journal name:
Nature Reviews Microbiology
Volume:
12,
Pages:
635–645
Year published:
DOI:
doi:10.1038/nrmicro3330
Published online

Abstract

Publicly available sequence databases of the small subunit ribosomal RNA gene, also known as 16S rRNA in bacteria and archaea, are growing rapidly, and the number of entries currently exceeds 4 million. However, a unified classification and nomenclature framework for all bacteria and archaea does not yet exist. In this Analysis article, we propose rational taxonomic boundaries for high taxa of bacteria and archaea on the basis of 16S rRNA gene sequence identities and suggest a rationale for the circumscription of uncultured taxa that is compatible with the taxonomy of cultured bacteria and archaea. Our analyses show that only nearly complete 16S rRNA sequences give accurate measures of taxonomic diversity. In addition, our analyses suggest that most of the 16S rRNA sequences of the high taxa will be discovered in environmental surveys by the end of the current decade.

At a glance

Figures

  1. Variable regions of the 16S ribosomal RNA.
    Figure 1: Variable regions of the 16S ribosomal RNA.

    Secondary structure of the 16S rRNA of Escherichia coli, as generated using the xrna program (see Further information). For our analysis, six R fragments of ~250 nucleotides were designed according to the known V regions (Supplementary information S2 (box)). In red, fragment R1 including regions V1 and V2; in orange, fragment R2 including region V3; in yellow, fragment R3 including region V4; in green, fragment R4 including regions V5 and V6; in blue, fragment R5 including regions V7 and V8; and in purple, fragment R6 including region V9.

  2. Predicting taxa richness using partial 16S ribosomal RNA sequences.
    Figure 2: Predicting taxa richness using partial 16S ribosomal RNA sequences.

    The 16S rDNA data set that was used was obtained from the Living Tree Project (LTP) release 108. Taxa recovery was approached using OTUs (operational taxonomic units) that were calculated using CD-HIT version 4.5 (Ref. 54). In all cases, the general taxonomic thresholds that were used for clustering are: 98.7% (species), 94.5% (genus), 86.5% (family), 82.0% (order), 78.5% (class) and 75.0% (phylum). a | Six R fragments of ~250 nucleotides were designed according to the V regions (Supplementary information S2 (box)); the results that were obtained for the full-length sequence are included for comparison. b | Based on the R fragments, four additional segments were created, all of which start at the 5′ end (that is, all including the V1 and V2 regions) but with different sizes: segment R1 contains the 250 nucleotides at the 5′ end, R1–R2 contains the 5′ 500 nucleotides, R1–R3 contains the 5′ 750 nucleotides, R1–R4 contains the 5′ 1050 nucleotides, R1–R5 contains the 5′ 1300 nucleotides, and 'full' corresponds to the full Escherichia coli 16S rRNA gene (which is 1,542 nucleotides). Analysis of the taxa recovery rate indicates a great underestimation of taxa richness when partial sequences are used. Although the situation tends to ameliorate as longer segments are considered, near full-length 16S rRNA genes sequences are required for accurate richness estimations and accurate classifications of high taxa.

  3. Classification of phylum Spirochaetes into candidate taxonomic units.
    Figure 3: Classification of phylum Spirochaetes into candidate taxonomic units.

    a | The phylum Spirochaetes is currently classified within one class (Spirochaetes), one order (Spirochaetales) and four families (Spirochaetaceae, Brevinemataceae, Brachyspiraceae and Leptospiraceae). A 16S ribosomal RNA phylogenetic reconstruction of the phylum Spirochaetes, based on 82 type strains obtained from the Living Tree Project (LTP) release 111 and using the RAxML algorithm55, shows a clear phylogenetic separation of five lineages within the phylum. Percentage bootstrap values are indicated next to the tree nodes. Scale bar indicates estimated sequence divergence. b | Distribution of the minimum sequence identity that is found in each bacterial and archaeal taxon in LTP release 102 (Supplementary information S1 (table) and Supplementary information S2 (box)). The average sequence identity among the five groups is shown as percentages and is linked to the density plot on the right-hand side to further confirm that the distances are within the values that are commonly displayed between taxa belonging to the rank of class. According to the strong monophyletic support and the low inter-clade sequence identities below the taxonomic threshold of 78.5% (Table 1), our analysis predicts five classes within Spirochaetes rather than one. The ten branches displayed in part a correspond to the following European Nucleotide Archive (ENA) accession numbers: Treponema maltophyla, X87140; Sphaerochaeta globosa, AF357916; Borrelia americana, EU081285; Spirochaeta litoralis, FR733665; Exilispira thermophila, AB364473; Brevinema andersonii, GU993264; Brachyspira aalborgi, Z22781; Leptospira interrogans, Z12817; Leptonema illini, AY714984; Turneriella parva, AY293856.

  4. Phylogenetic reconstruction of the SAR11 group within the Proteobacteria based on 16S ribosomal RNA gene sequences.
    Figure 4: Phylogenetic reconstruction of the SAR11 group within the Proteobacteria based on 16S ribosomal RNA gene sequences.

    The reconstruction was based on Living Tree Project (LTP) release 111. Several phyla and the major alphaproteobacterial families are shown for reference. The CTU (candidate taxonomic unit) analysis that was carried out on the SAR11 group, which was suggested to form a coherent taxon within the class Alphaproteobacteria, revealed the existence of three classes, SAR11.Class1, SAR11.Class1-1 and SAR11.Class2. One class, SAR11.Class2, is composed of two candidate orders (SAR11.Order2 and SAR11.Order3; yellow). The pie charts indicate the percentage of genera that comprise only surface-water sequences (orange), only deep-water sequences (purple), both surface-water and deep-water sequences (green) and other samples (grey). The ecological coherence with respect to the site of sequence retrieval is inversely correlated with the rank of the taxon. In addition to the large phylogenetic depth of Alphaproteobacteria, the positions of classes Epsilonproteobacteria and Deltaproteobacteria in this tree reconstruction strongly suggest that the phylum Proteobacteria is not monophyletic. Scale bar represents estimated sequence divergence.

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Author information

Affiliations

  1. Marine Microbiology Group, Department of Ecology and Marine Resources, Mediterranean Institute for Advanced Studies (Spanish National Research Council (CSIC)-University of the Balearic Islands (UIB)), E-07190 Esporles, Balearic Islands, Spain.

    • Pablo Yarza &
    • Ramon Rosselló-Móra
  2. Max Planck Institute for Marine Microbiology, Celsiusstrasse 1, D-28359 Bremen, Germany.

    • Pablo Yarza,
    • Pelin Yilmaz,
    • Elmar Pruesse,
    • Frank Oliver Glöckner &
    • Rudolf Amann
  3. Ribocon GmbH, Fahrenheitstrasse 1, D-28359 Bremen, Germany.

    • Pablo Yarza
  4. Jacobs University Bremen, Campus Ring 1, D-28759 Bremen, Germany.

    • Frank Oliver Glöckner
  5. Lehrstuhl für Mikrobiologie, Technische Universität München, D-85350 Freising, Germany.

    • Wolfgang Ludwig &
    • Karl-Heinz Schleifer
  6. Department of Microbiology, University of Georgia, 527 Biological Sciences Building, Athens, Georgia 30605–2605, USA.

    • William B. Whitman
  7. Société de Bactériologie Systématique et Vétérinaire (SBSV) and École Nationale Vétérinaire de Toulouse (ENVT), F-31076 Toulouse cedex 03, France.

    • Jean Euzéby

Competing interests statement

The authors declare no competing interests.

Corresponding authors

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Author details

  • Pablo Yarza

    Pablo Yarza received his Ph.D. in environmental microbiology and biotechnology from the University of the Balearic Islands, Spain, in 2011. He is currently a postdoctoral researcher at the company Ribocon GmbH in Bremen, Germany. His main interests are the development and analysis of curated sequence databases in the frameworks of microbial systematics and biotechnology.

  • Pelin Yilmaz

    Pelin Yilmaz did her Ph.D. in bioinformatics at the Microbial Genomics and Bioinformatics Group at the Max Planck Institute for Marine Microbiology, Bremen, Germany. She is currently a postdoctoral researcher in this group, focusing on bacterial and archaeal phylogeny and taxonomy, as well as microbial diversity and function in marine ecosystems.

  • Elmar Pruesse

    Elmar Pruesse received his Ph.D. in bioinformatics from the Jacobs University, Bremen, Germany, in 2011. He is currently a postdoctoral researcher in the Microbial Genomics and Bioinformatics group at the Max Planck Institute for Marine Microbiology, Bremen, Germany. His main research interest is the development of scalable methods for the integrative analysis of sequence and contextual data.

  • Frank Oliver Glöckner

    Frank Oliver Glöckner received his Ph.D. in microbiology from the Technical University Munich, Germany, in 1998. He is Head of the Microbial Genomics and Bioinformatics Research Group at the Max Planck Institute for Marine Microbiology in Bremen, Germany, and Professor of Bioinformatics at Jacobs University Bremen, Germany. His group develops enabling technologies and products to transform the wealth of environmental sequence and contextual (meta)data into biological knowledge.

  • Wolfgang Ludwig

    Wolfgang Ludwig received his Ph.D. in microbiology from the Technical University Munich, Germany, in 1981. His research interests focus on the phylogeny and systematics of bacteria and archaea, as well as bioinformatics tools for phylogeny and identification studies.

  • Karl-Heinz Schleifer

    Karl-Heinz Schleifer received his doctoral degree in microbiology from the Technical University Munich (TUM), Germany, in 1967. He was Head of the Department of Microbiology at the TUM from 1974 until 2007. Since 2007, he has been TUM Emeritus of Excellence. He is mainly interested in systematics and molecular ecology of bacteria.

  • William B. Whitman

    William B. Whitman is a professor at the University of Georgia, Athens, USA. He did postdoctoral studies at the University of Illinois at Urbana, USA, and did his doctoral research at the University of Texas at Austin, USA. His laboratory studies the systematics and physiology of free-living bacteria and archaea that catalyse biogeochemically important transformations.

  • Jean Euzéby

    Jean P. Euzéby was a professor at the Ecole Nationale Vétérinaire de Toulouse, France (he retired in June 2013). In 1997, he established the List of Prokaryotic Names with Standing in Nomenclature (LPSN).

  • Rudolf Amann

    Rudolf Amann received his doctoral degree in microbiology from the Technical University Munich, Germany, in 1988. He is currently Head of the Department of Molecular Ecology at the Max Planck Institute for Marine Microbiology, Bremen, Germany, and Professor of Microbial Ecology at the University of Bremen, Germany. His research focus is the analysis of the diversity, composition and function of microbial communities by nucleic acid-based methods.

  • Ramon Rosselló-Móra

    Ramon Rosselló-Móra received his Ph.D. in biology from the University of the Balearic Islands (UIB), Spain, in 1992. He is currently a researcher and Head of the Marine Microbiology Group at the Mediterranean Institute for Advanced Studies (IMEDEA) (Spanish National Research Council-UIB). His research focuses on microbial molecular ecology studies on hypersaline environments, as well as the development of modern tools that can be applied to microbial taxonomy.

Supplementary information

Excel files

  1. Supplementary information S1 (table) (114 KB)

    Intra-taxon sequence identity measures used to calculate the taxonomic thresholds.

  2. Supplementary information S4 (table) (1,080 KB)

    Sequence associated meta-data including CTU classification. Fields: acc,start,stop,tax_CTU,tax_xref_embl

PDF files

  1. Supplementary information S2 (Box) (177 KB)

    Additional tables and figures.

  2. Supplementary information S3 (figure) (11,625 KB)

    Phylogenetic reconstruction of 15 candidate divisions and environmental clades

Additional data