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Front. Microbiol. | doi: 10.3389/fmicb.2018.03165

Identification of microbial dark matter in Antarctic environments

  • 1Scripps Institution of Oceanography, University of California, San Diego, United States
  • 2Center for Microbiome Innovation, University of California, San Diego, United States

Numerous studies have applied molecular techniques to understand the diversity, evolution, and ecological function of Antarctic bacteria and archaea. One common technique is sequencing of the 16S rRNA gene, which produces a nearly-quantitative profile of community membership. However, the utility of this and similar approaches is limited by what is known about the evolution, physiology, and ecology of surveyed taxa. When representative genomes are available in public databases some of this information can be gleaned from genomic studies, and automated pipelines exist to carry out this task. Here the paprica metabolic inference pipeline was used to assess how well Antarctic microbial communities are represented by the available completed genomes. The NCBI’s Sequence Read Archive (SRA) was searched for Antarctic datasets that used one of the Illumina platforms to sequence the 16S rRNA gene. These data were quality controlled and denoised to identify unique reads, then analyzed with paprica to determine the degree of overlap with the closest phylogenetic neighbor with a completely sequenced genome. While some unique reads had perfect mapping to 16S rRNA genes from completed genomes, the mean percent overlap for all mapped reads was 86.6 %. When samples were grouped by environment, some environments appeared more or less well represented by the available genomes. For the domain Bacteria, seawater was particularly poorly represented with a mean overlap of 80.2 %, while for the domain Archaea glacial ice was particularly poorly represented with an overlap of only 48.0 % for a single sample. These findings suggest that a considerable effort is needed to improve the representation of Antarctic microbes in genome sequence databases.

Keywords: Glacier, Snow, Ice, Antarctica, Permafrost, 16S rRNA, Seawater, lake

Received: 01 Sep 2018; Accepted: 06 Dec 2018.

Edited by:

Anne D. Jungblut, Natural History Museum, United Kingdom

Reviewed by:

Charles K. Lee, University of Waikato, New Zealand
Vincent Delafont, University of Poitiers, France  

Copyright: © 2018 Bowman. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Prof. Jeff S. Bowman, Scripps Institution of Oceanography, University of California, San Diego, La Jolla, United States,