Microbial community assembly and evolution in subseafloor sediment

Piotr Starnawski, Thomas Bataillon, Thijs J.G. Ettema, Lara M. Jochum, Lars Schreiber, Xihan Chen, Mark A. Lever, Martin F. Polz, Bo B. Jørgensen, Andreas Schramm, Kasper U. Kjeldsen*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

129 Citations (Scopus)


Bacterial and archaeal communities inhabiting the subsurface seabed live under strong energy limitation and have growth rates that are orders of magnitude slower than laboratory-grown cultures. It is not understood how subsurface microbial communities are assembled and whether populations undergo adaptive evolution or accumulate mutations as a result of impaired DNA repair under such energy-limited conditions. Here we use amplicon sequencing to explore changes of microbial communities during burial and isolation from the surface to the >5,000-y-old subsurface of marine sediment and identify a small core set of mostly uncultured bacteria and archaea that is present throughout the sediment column. These persisting populations constitute a small fraction of the entire community at the surface but become predominant in the subsurface. We followed patterns of genome diversity with depth in four dominant lineages of the persisting populations by mapping metagenomic sequence reads onto single-cell genomes. Nucleotide sequence diversity was uniformly low and did not change with age and depth of the sediment. Likewise, therewas no detectable change inmutation rates and efficacy of selection. Our results indicate that subsurface microbial communities predominantly assemble by selective survival of taxa able to persist under extreme energy limitation.

Original languageEnglish
Pages (from-to)2940-2945
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Issue number11
Publication statusPublished - 14 Mar 2017
Externally publishedYes


  • Bacteria
  • Evolution
  • Marine sediment
  • Metagenomics
  • Single-cell genomics


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