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      Ecology of the rare microbial biosphere of the Arctic Ocean.

      Proceedings of the National Academy of Sciences of the United States of America

      Water Microbiology, microbiology, Seawater, isolation & purification, genetics, RNA, Ribosomal, 16S, RNA, Bacterial, RNA, Archaeal, Phylogeny, Oceans and Seas, Ecosystem, classification, Bacteria, Arctic Regions, Archaea

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          Abstract

          Understanding the role of microbes in the oceans has focused on taxa that occur in high abundance; yet most of the marine microbial diversity is largely determined by a long tail of low-abundance taxa. This rare biosphere may have a cosmopolitan distribution because of high dispersal and low loss rates, and possibly represents a source of phylotypes that become abundant when environmental conditions change. However, the true ecological role of rare marine microorganisms is still not known. Here, we use pyrosequencing to describe the structure and composition of the rare biosphere and to test whether it represents cosmopolitan taxa or whether, similar to abundant phylotypes, the rare community has a biogeography. Our examination of 740,353 16S rRNA gene sequences from 32 bacterial and archaeal communities from various locations of the Arctic Ocean showed that rare phylotypes did not have a cosmopolitan distribution but, rather, followed patterns similar to those of the most abundant members of the community and of the entire community. The abundance distributions of rare and abundant phylotypes were different, following a log-series and log-normal model, respectively, and the taxonomic composition of the rare biosphere was similar to the composition of the abundant phylotypes. We conclude that the rare biosphere has a biogeography and that its tremendous diversity is most likely subjected to ecological processes such as selection, speciation, and extinction.

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          Most cited references 42

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          MUSCLE: multiple sequence alignment with high accuracy and high throughput.

           Robert Edgar (2004)
          We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.
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            Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy.

            The Ribosomal Database Project (RDP) Classifier, a naïve Bayesian classifier, can rapidly and accurately classify bacterial 16S rRNA sequences into the new higher-order taxonomy proposed in Bergey's Taxonomic Outline of the Prokaryotes (2nd ed., release 5.0, Springer-Verlag, New York, NY, 2004). It provides taxonomic assignments from domain to genus, with confidence estimates for each assignment. The majority of classifications (98%) were of high estimated confidence (> or = 95%) and high accuracy (98%). In addition to being tested with the corpus of 5,014 type strain sequences from Bergey's outline, the RDP Classifier was tested with a corpus of 23,095 rRNA sequences as assigned by the NCBI into their alternative higher-order taxonomy. The results from leave-one-out testing on both corpora show that the overall accuracies at all levels of confidence for near-full-length and 400-base segments were 89% or above down to the genus level, and the majority of the classification errors appear to be due to anomalies in the current taxonomies. For shorter rRNA segments, such as those that might be generated by pyrosequencing, the error rate varied greatly over the length of the 16S rRNA gene, with segments around the V2 and V4 variable regions giving the lowest error rates. The RDP Classifier is suitable both for the analysis of single rRNA sequences and for the analysis of libraries of thousands of sequences. Another related tool, RDP Library Compare, was developed to facilitate microbial-community comparison based on 16S rRNA gene sequence libraries. It combines the RDP Classifier with a statistical test to flag taxa differentially represented between samples. The RDP Classifier and RDP Library Compare are available online at http://rdp.cme.msu.edu/.
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              SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB

              Sequencing ribosomal RNA (rRNA) genes is currently the method of choice for phylogenetic reconstruction, nucleic acid based detection and quantification of microbial diversity. The ARB software suite with its corresponding rRNA datasets has been accepted by researchers worldwide as a standard tool for large scale rRNA analysis. However, the rapid increase of publicly available rRNA sequence data has recently hampered the maintenance of comprehensive and curated rRNA knowledge databases. A new system, SILVA (from Latin silva, forest), was implemented to provide a central comprehensive web resource for up to date, quality controlled databases of aligned rRNA sequences from the Bacteria, Archaea and Eukarya domains. All sequences are checked for anomalies, carry a rich set of sequence associated contextual information, have multiple taxonomic classifications, and the latest validly described nomenclature. Furthermore, two precompiled sequence datasets compatible with ARB are offered for download on the SILVA website: (i) the reference (Ref) datasets, comprising only high quality, nearly full length sequences suitable for in-depth phylogenetic analysis and probe design and (ii) the comprehensive Parc datasets with all publicly available rRNA sequences longer than 300 nucleotides suitable for biodiversity analyses. The latest publicly available database release 91 (August 2007) hosts 547 521 sequences split into 461 823 small subunit and 85 689 large subunit rRNAs.
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                Author and article information

                Journal
                10.1073/pnas.0908284106
                2796907
                20018741

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